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PHD Project - Driver energy prediction
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Diss/02_code/00_RawData_Python/sklearn-rerun_JZ.ipynb

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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Setup\n",
"\n",
"`TRAINING_RANGE` und `TEST_RANGE` müssen je nach Länge des Datensatzes angepasst werden.\n",
"\n",
"**Keine Anpassung erforderlich** (Siehe Datensatz herunterladen)\n",
"- 30% Training-Daten (0-30%)\n",
"- 70% Test-Daten (30%-100%)"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"416"
]
},
"execution_count": 1,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"INPUT_FILE = 'data.csv'\n",
"TARGET_COLUMN = 'flt_obd_speed'\n",
"# Still contains positional information and acceleration; however we currently train\n",
"# sample by sample without knowledge of previous or other data, so it should not be\n",
"# possible for the Regressor to simply \"calculate\" the speed.\n",
"EXCLUDED_COLUMNS = ('flt_gps_speed', 'flt_obd_engine_load', 'flt_obd_engine_rpm',\n",
" 'flt_obd_maf', 'flt_obd_accelerator_pedal','flt_time','flt_time_system_clock',\n",
" 'flt_time_utc','flt_ax','flt_ay','flt_az','flt_gx','flt_gy','flt_gz','flt_compass',\n",
" 'flt_number_of_satelites','flt_accuracy','flt_gps_bearing','flt_calc_dist_gps',\n",
" 'flt_calc_dist_vt','flt_calc_ax_vt','flt_timeIP',\n",
" 'weat_latitude','weat_longitude','weat_distanceIP','weat_timeIP','weat_join_idx',\n",
" 'hAccel_1','hAccel_2','hAccel_3','flt_mAccel_1','flt_mAccel_2','flt_mAccel_3',\n",
" 'flt_mGier_1','flt_mGier_2','flt_mGier_3','rot_Accel_1','rot_Accel_2','rot_Accel_3',\n",
" 'rot_Gier_1','rot_Gier_2','rot_Gier_3','rot_Accel_flt_1','rot_Accel_flt_2','rot_Accel_flt_3',\n",
" 'rot_Gier_flt_1','rot_Gier_flt_2','rot_Gier_flt_3'\n",
" )\n",
"# See explanation below the feature importance plot\n",
"OVERFITTING_COLUMNS = ('weat_temperature', 'weat_humidity', 'join_idx', 'weat_windBearing', 'weat_windSpeed',\n",
" #'latitude', 'longitude', 'flt_latitude', 'flt_longitude',\n",
" 'ors_percentage_cumsum', 'flt_obd_air_temperature',\n",
" 'mb_step_weight')\n",
"# Since there are a lot of fields containing those\n",
"# Note: This breaks the map plotting\n",
"OVERFITTING_SUBWORDS = ('distance', 'remainDistance', 'remainDistanze', 'cumsumDistance', 'segDistance', 'time', 'remainTime')\n",
"\n",
"from runsql import runsql\n",
"DATA_COLUMNS = [c['Field']\n",
" for c in runsql('show columns from computeddata')\n",
" if c['Type'] == 'double'\n",
" and c['Field'] != TARGET_COLUMN\n",
" #and c['Field'] not in EXCLUDED_COLUMNS\n",
" #and c['Field'] not in OVERFITTING_COLUMNS\n",
" #and not any([w in c['Field'] for w in OVERFITTING_SUBWORDS])\n",
" ]\n",
"len(DATA_COLUMNS)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Datensatz herunterladen\n",
"\n",
"`SETUP_ID` anpassen, Rest läuft automatisch.\n",
"\n",
"Einige Datensätze besitzen keinen Eintrag für `flt_obd_speed`. Für eine Liste der Datensätze *mit* diesem Wert kann beispielsweise folgende SQL-Abfrage verwendet werden (Achtung, braucht (prinzipbedingt) sehr lange!):\n",
"\n",
"```sql\n",
"select setup_id s, count(*) n\n",
"from computeddata\n",
"group by s\n",
"having not exists (\n",
" select *\n",
" from computeddata\n",
" where setup_id = s\n",
" and flt_obd_speed is null)\n",
"order by n asc\n",
"```"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"SETUP_ID = 868\n",
"import csv\n",
"from runsql import runsql\n",
"reader = runsql('select * from computeddata where setup_id = {} order by distance asc'.format(SETUP_ID))\n",
"reader_data = list(reader) # list(...) so that following cells can be repeated"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"import math\n",
"data = []\n",
"target = []\n",
"for row in reader_data:\n",
" data += [[float(row[c]) if row[c] != '' else math.nan for c in DATA_COLUMNS]]\n",
" target += [float(row[TARGET_COLUMN])] # Errors if NaN in TARGET_COLUMN"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"tr_st = 0\n",
"tr_ed = math.floor(len(data)*0.3)\n",
"TRAINING_RANGE = (tr_st, tr_ed)\n",
"TEST_RANGE = (tr_ed, len(data)) # TEST_RANGE = (len(data)-tr_ed, len(data))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Leere Zellen füllen\n",
"\n",
"Da nicht alle Datensätze alle Spalten haben – gäbe sicherlich bessere Strategien, aber das funktioniert erstaunlich gut (wahrscheinlich sind die \"wichtigen\" Spalten immer vorhanden)."
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(7228, 416)"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from sklearn.impute import SimpleImputer\n",
"imp = SimpleImputer(strategy='constant', fill_value=0) # Other strategies remove fully null columns\n",
"data = imp.fit_transform(data)\n",
"import numpy as np\n",
"np.shape(data)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Analyze INPUT DATA\n",
"Eingangsdaten analysieren"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"scrolled": false
},
"outputs": [
{
"data": {
"text/html": [
"<div><i>Table length=7228</i>\n",
"<table id=\"table140522945280080\" class=\"table-striped table-bordered table-condensed\">\n",
"<thead><tr><th>distance</th><th>latitude</th><th>longitude</th><th>time</th><th>join_idx</th><th>curvature</th><th>radius</th><th>phiSegment</th><th>flt_DB_counter</th><th>flt_setup_id</th><th>flt_time</th><th>flt_time_system_clock</th><th>flt_time_utc</th><th>flt_latitude</th><th>flt_longitude</th><th>flt_altitude</th><th>flt_gps_speed</th><th>flt_ax</th><th>flt_ay</th><th>flt_az</th><th>flt_gx</th><th>flt_gy</th><th>flt_gz</th><th>flt_compass</th><th>flt_number_of_satelites</th><th>flt_accuracy</th><th>flt_gps_bearing</th><th>flt_obd_engine_load</th><th>flt_obd_engine_rpm</th><th>flt_obd_maf</th><th>flt_obd_accelerator_pedal</th><th>flt_obd_air_temperature</th><th>flt_calc_dist_gps</th><th>flt_calc_dist_vt</th><th>flt_calc_ax_vt</th><th>flt_go_elevation</th><th>flt_go_eleResolution</th><th>flt_distanceIP</th><th>flt_timeIP</th><th>flt_osm_trafficSignal</th><th>flt_osm_w_wood</th><th>flt_join_idx</th><th>flt_curvature</th><th>flt_radius</th><th>flt_phiSegment</th><th>hr_latitude</th><th>hr_longitude</th><th>hr_elevation</th><th>hr_distance</th><th>hr_SpeedLimit</th><th>hr_LinkID</th><th>hr_shapeFirstPoint</th><th>hr_shapeLastPoint</th><th>hr_lengthSegemnt</th><th>hr_remainDistanze</th><th>hr_remainTime</th><th>hr_actualManeuver</th><th>hr_traficSpeed</th><th>hr_traficTime</th><th>hr_baseSpeed</th><th>hr_baseTime</th><th>hr_JamFactor</th><th>hr_FunctionalRoadClass</th><th>hr_consumption</th><th>hr_mTravelTime</th><th>hr_mLenght</th><th>hr_mFirstPoint</th><th>hr_mLastPoint</th><th>hr_mNextManeuver</th><th>hr_mTrafficTime</th><th>hr_mStartAngle</th><th>hr_leg_firtPoint</th><th>hr_leg_lastPoint</th><th>hr_leg_length</th><th>hr_leg_travelTime</th><th>hr_leg_trafficTime</th><th>hr_leg_baseTime</th><th>hr_leg_spot</th><th>hr_leg_shapeIndex</th><th>hr_IdxNP</th><th>hr_NearestPoint_1</th><th>hr_NearestPoint_2</th><th>hr_PointOnRoute_1</th><th>hr_PointOnRoute_2</th><th>hr_Dist2Origin</th><th>hr_Dist2Route</th><th>hr_distance_lldist</th><th>hr_osm_trafficSignal</th><th>hr_osm_w_wood</th><th>hr_distanceIP</th><th>hr_join_idx</th><th>hr_curvature</th><th>hr_radius</th><th>hr_phiSegment</th><th>go_start_latitude</th><th>go_start_longitude</th><th>go_end_latitude</th><th>go_end_longitude</th><th>go_distance</th><th>go_duration</th><th>go_latitude</th><th>go_longitude</th><th>go_routing_flag</th><th>go_mean_velocity_calc_pre</th><th>go_mean_velocity_calc</th><th>go_cum_distance</th><th>go_IdxNP</th><th>go_NearestPoint_1</th><th>go_NearestPoint_2</th><th>go_PointOnRoute_1</th><th>go_PointOnRoute_2</th><th>go_Dist2Origin</th><th>go_Dist2Route</th><th>go_distanceIP</th><th>go_join_idx</th><th>go_curvature</th><th>go_radius</th><th>go_phiSegment</th><th>osrm_latitude</th><th>osrm_longitude</th><th>osrm_seg_datasources</th><th>osrm_seg_weight</th><th>osrm_seg_distance</th><th>osrm_seg_duration</th><th>osrm_seg_nodeID</th><th>osrm_step_weight</th><th>osrm_step_duration</th><th>osrm_step_distance</th><th>osrm_mn_bearing_before</th><th>osrm_mn_bearing_after</th><th>osrm_mn_exit</th><th>osrm_i_lanes_valid_1</th><th>osrm_i_lanes_valid_2</th><th>osrm_i_lanes_valid_3</th><th>osrm_i_lanes_valid_4</th><th>osrm_i_lanes_valid_5</th><th>osrm_i_lanes_valid_6</th><th>osrm_i_bearings_1</th><th>osrm_i_bearings_2</th><th>osrm_i_bearings_3</th><th>osrm_i_bearings_4</th><th>osrm_i_bearings_5</th><th>osrm_i_bearings_6</th><th>osrm_i_entry_1</th><th>osrm_i_entry_2</th><th>osrm_i_entry_3</th><th>osrm_i_entry_4</th><th>osrm_i_entry_5</th><th>osrm_i_entry_6</th><th>osrm_i_in</th><th>osrm_i_out</th><th>osrm_i_laneNumber</th><th>osrm_seg_speed</th><th>osrm_segDistance_lldist</th><th>osrm_seg_cumsumDistance</th><th>osrm_IdxNP</th><th>osrm_NearestPoint_1</th><th>osrm_NearestPoint_2</th><th>osrm_PointOnRoute_1</th><th>osrm_PointOnRoute_2</th><th>osrm_Dist2Origin</th><th>osrm_Dist2Route</th><th>osrm_distanceIP</th><th>osrm_join_idx</th><th>osrm_curvature</th><th>osrm_radius</th><th>osrm_phiSegment</th><th>ors_latitude</th><th>ors_longitude</th><th>ors_elevation</th><th>ors_long_distance</th><th>ors_long_duration</th><th>ors_ascent_route</th><th>ors_descent_rout
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"<tr><td>25.0</td><td>48.7436932112327</td><td>11.43648197635</td><td>13.5999896459859</td><td>6.0</td><td>-0.0353585292273567</td><td>10000.0</td><td>-0.0035381684558074</td><td>15425543.0</td><td>868.0</td><td>1544811302505.0</td><td>24820948.0</td><td>1544811303000.0</td><td>48.7437022982964</td><td>11.4364807019015</td><td>412.449004455377</td><td>2.28309</td><td>0.0287304203957319</td><td>1.54186594486237</td><td>9.98860931396484</td><td>0.0146607663482428</td><td>-0.0109955742955208</td><td>-0.0916297882795334</td><td>107.509994506836</td><td>10.0</td><td>4.0</td><td>352.704071044922</td><td>57.0</td><td>872.0</td><td>4.49</td><td>26.3</td><td>0.0</td><td>26.0147474441197</td><td>14.4177779555321</td><td>0.298364961852885</td><td>368.320342091593</td><td>19.087904</td><td>26.0147474441197</td><td>13.971</td><td>0.0</td><td>0.0</td><td>6.0</td><td>-0.0536878174355847</td><td>10000.0</td><td>-0.00539094936142553</td><td>0.0</td><td>0.0</td><td>414.0</td><td>-103.333333333333</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>36198.3333333333</td><td>2145.44444444444</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>-103.628117170894</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>-6.76428974196913e-09</td><td>10000.0</td><td>-3.67342784345882e-09</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>4.72222222222222</td><td>4.22857142857143</td><td>431.397260273973</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>-3.29935555992962e-08</td><td>10000.0</td><td>-1.97323605266641e-09</td><td>0.0</td><td>0.0</td><td>0.0</td><td>4.3</td><td>0.0</td><td>0.0</td><td>466244469.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>1.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>2.24691305866331</td><td>41.3892491809247</td><td>41.4009270480988</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>-0.00396132082064093</td><td>10000.0</td><td>-0.000414107028607448</td><td>0.0</td><td>0.0</td><td>368.492641936263</td><td>872.061538461538</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>26.16</td><td>0.0</td><td>0.0</td><td>11.0</td><td>0.0</td><td>0.0</td><td>4.17098445595855</td><td>7.26640316205534</td><td>8.25906622722696</td><td>8.25641025641026</td><td>919.2</td><td>2.59</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0145549446043223</td><td>68.7051709484102</td><td>0.00143205018618015</td><td>2.0</td><td>0.0</td><td>0.0</td><td>20.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>2.0</td><td>20.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>-0.00396132082064093</td><td>10000.0</td><td>-0.000414107028607448</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>12.0789473684211</td><td>18.2142857142857</td><td>5.42857142857143</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>-0.000328642083029717</td><td>10000.0</td><td>-3.36379225300824e-05</td><td>-0.950388589851387</td><td>0.0</td><td>0.69</td><td>1.76883033186317</td><td>99.9584681163598</td><td>9.46428878316838</td><td>1.0</td><td>1544770869.93001</td><td>1544800767.03887</td><td>48.7437022982964</td><td>11.4364807019015</td><td>26
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"<tr><td>36130.0</td><td>48.4939694137251</td><td>11.3572322859319</td><td>1829.33621509764</td><td>7227.0</td><td>-0.056623105735224</td><td>10000.0</td><td>-0.00566790533279996</td><td>15456110.0</td><td>868.0</td><td>1544813123714.0</td><td>26646933.0</td><td>1544813129000.0</td><td>48.4939552345631</td><td>11.3572287793272</td><td>516.280680220879</td><td>0.0</td><td>-0.78529816865921</td><td>1.48440504074097</td><td>9.59596061706543</td><td>0.00244346098043025</td><td>0.00366519158706069</td><td>0.0268780700862408</td><td>8.34000015258789</td><td>8.0</td><td>4.0</td><td>222.467391967773</td><td>2.0</td><td>953.0</td><td>13.52</td><td>14.5</td><td>-3.0</td><td>36128.4023150731</td><td>36815.9979171885</td><td>0.0</td><td>466.492992834383</td><td>19.087904</td><td>36128.4023150731</td><td>1835.18</td><td>0.0</td><td>0.0</td><td>7227.0</td><td>-0.0930131572675051</td><td>10000.0</td><td>-0.00942142143901802</td><td>0.0</td><td>0.0</td><td>511.996829328612</td><td>36012.3076923077</td><td>50.00000148</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>157.0</td><td>10.0</td><td>0.0</td><td>7.7777781</td><td>0.0</td><td>7.7777781</td><td>0.0</td><td>-1.0</td><td>5.0</td><td>48.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>36020.5727560715</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>-0.00101243873651327</td><td>10000.0</td><td>-0.000101567129630762</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>5.75</td><td>5.75</td><td>35905.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>1.7005751341119e-07</td><td>10000.0</td><td>9.69548543219796e-09</td><td>0.0</td><td>0.0</td><td>0.0</td><td>9.9</td><td>0.0</td><td>0.0</td><td>5196637536.0</td><td>48.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>1.0</td><td>1.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>2.0</td><td>6.12102054494306</td><td>36200.2422457066</td><td>36210.4560486315</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>-1.04699504943255e-07</td><td>10000.0</td><td>-5.30854712744824e-09</td><td>0.0</td><td>0.0</td><td>3584.01785714443</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>51.95</td><td>0.0</td><td>0.0</td><td>10.0</td><td>0.0</td><td>0.0</td><td>11.1071428571429</td><td>14.4315196998124</td><td>36125.4847078342</td><td>42632.3999999999</td><td>35541.6</td><td>99.99</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>-3.83465653268911e-08</td><td>10000.0</td><td>1.54059471917377e-09</td><td>3.0</td><td>0.0</td><td>0.0</td><td>50.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>1.0</td><td>50.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>-1.04699504943255e-07</td><td>10000.0</td><td>-5.30854712744824e-09</td><td>48.49403</td><td>11.35718</td><td>0.0</td><td>0.0</td><td>16.7142857142857</td><td>166.0</td><td>33.5</td><td>1829.0</td><td>48.4939552345631</td><td>11.3572287793272</td><td>48.493961416713</td><td>11.3572363090598</td><td>36127.5189030374</td><td>8.68185746441715</td><td>36128.4023150731</td><td>7227.0</td><td>0.00139203991245897</td><td>718.370325310476</td><td>0.000139776242855112</td><td>-1.91949136196197</td><td>0.0</td><td>0.740783734856378</td><td>1.67</td><td>80.843130271765</td><td>10.01</td><td>1.0</td><td>1544770823.66496</td><td>1544800852.65324</td><td>48.4939552345631</td><
"<tr><td>36135.0</td><td>48.4940105661686</td><td>11.3572265430113</td><td>1837.57304569241</td><td>7228.0</td><td>0.0</td><td>10000.0</td><td>0.0</td><td>15456273.0</td><td>868.0</td><td>1544813132761.0</td><td>26655980.0</td><td>1544813138000.0</td><td>48.4940366768798</td><td>11.3571913926126</td><td>515.895603237607</td><td>0.0</td><td>-0.593762040138245</td><td>1.01514148712158</td><td>9.64384460449219</td><td>0.00122173049021512</td><td>0.0</td><td>0.00244346098043025</td><td>0.779999971389771</td><td>8.0</td><td>4.0</td><td>222.467391967773</td><td>18.0</td><td>827.0</td><td>6.99</td><td>14.5</td><td>-3.0</td><td>36138.8908448501</td><td>36820.9930560986</td><td>0.0</td><td>466.669867561766</td><td>19.087904</td><td>36138.8908448501</td><td>1844.227</td><td>0.0</td><td>0.0</td><td>7228.0</td><td>0.0</td><td>10000.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>512.009610431538</td><td>36017.6153846154</td><td>50.00000148</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>157.0</td><td>10.0</td><td>0.0</td><td>7.7777781</td><td>0.0</td><td>7.7777781</td><td>0.0</td><td>-1.0</td><td>5.0</td><td>48.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>36025.821026925</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>10000.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>5.75</td><td>5.75</td><td>35906.6428571429</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>10000.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>9.9</td><td>0.0</td><td>0.0</td><td>5196637536.0</td><td>48.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>1.0</td><td>1.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>2.0</td><td>6.12102054494306</td><td>36206.3003467689</td><td>36216.515858971</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>10000.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>3708.02434895997</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>51.95</td><td>0.0</td><td>0.0</td><td>10.0</td><td>0.0</td><td>0.0</td><td>11.1071428571429</td><td>14.4315196998124</td><td>36133.3184010307</td><td>42725.7</td><td>35541.6</td><td>99.99</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>10000.0</td><td>0.0</td><td>3.0</td><td>0.0</td><td>0.0</td><td>50.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>1.0</td><td>50.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>10000.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>16.7142857142857</td><td>168.571428571429</td><td>33.8928571428571</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>10000.0</td><td>0.0</td><td>-1.91928789617554</td><td>0.0</td><td>0.740787533770754</td><td>1.67</td><td>80.8321122176761</td><td>10.01</td><td>1.0</td><td>1544770823.63332</td><td>1544800852.67849</td><td>48.4940366768798</td><td>11.3571913926126</td><td>36138.8908448501</td><td>1844.227</td><td>7228.0</td><td>0.0</td><td>10000.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>6.1</td><td>0.0</td><td>0.0</td><td>48.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>
"</table></div>"
],
"text/plain": [
"<Table length=7228>\n",
"distance latitude ... rot_Gier_flt_2 rot_Gier_flt_3 \n",
"float64 float64 ... float64 float64 \n",
"-------- ---------------- ... -------------------- -------------------\n",
" 0.0 48.7436851684512 ... 0.00124893632174478 0.00147046360145099\n",
" 5.0 48.743660011792 ... 0.0029062661334533 0.0694993957818311\n",
" 10.0 48.7436454613238 ... 0.00300525107095361 0.103801841905125\n",
" 15.0 48.7436203018653 ... 0.000730703525049424 0.0883675689058716\n",
" 20.0 48.7436491772175 ... -0.00357387413653213 0.0333486709761538\n",
" 25.0 48.7436932112327 ... -0.00851107271491372 -0.0301408279789142\n",
" ... ... ... ... ...\n",
" 36105.0 48.4940887159834 ... 0.00740829081028163 -0.0548438650170325\n",
" 36110.0 48.4940565365702 ... 0.00288670405737579 -0.0195602248573346\n",
" 36115.0 48.4940309552407 ... -0.00194797214075882 0.0269558346376725\n",
" 36120.0 48.4940086969898 ... -0.00538678413555656 0.0628600177075434\n",
" 36125.0 48.493979044084 ... -0.00645971524083978 0.0715674259210277\n",
" 36130.0 48.4939694137251 ... -0.00519217308017079 0.0494020270730009\n",
" 36135.0 48.4940105661686 ... -0.0024982680467088 0.0071301850944708"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Convert to Table\n",
"import sys\n",
"from astropy.table import Table\n",
"t = Table(data, names=DATA_COLUMNS)\n",
"lat = t['latitude']\n",
"lng = t['longitude']\n",
"# Subsampling ... use points every 50m for plotting\n",
"lat = lat[::10]\n",
"lng = lng[::10]\n",
"# determine range to print based on min, max lat and lon of the data\n",
"margin = 0 # buffer to add to the range\n",
"lat_min = min(lat) - margin\n",
"lat_max = max(lat) + margin\n",
"lon_min = min(lng) - margin\n",
"lon_max = max(lng) + margin\n",
"t"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['distance',\n",
" 'latitude',\n",
" 'longitude',\n",
" 'time',\n",
" 'join_idx',\n",
" 'curvature',\n",
" 'radius',\n",
" 'phiSegment',\n",
" 'flt_DB_counter',\n",
" 'flt_setup_id',\n",
" 'flt_time',\n",
" 'flt_time_system_clock',\n",
" 'flt_time_utc',\n",
" 'flt_latitude',\n",
" 'flt_longitude',\n",
" 'flt_altitude',\n",
" 'flt_gps_speed',\n",
" 'flt_ax',\n",
" 'flt_ay',\n",
" 'flt_az',\n",
" 'flt_gx',\n",
" 'flt_gy',\n",
" 'flt_gz',\n",
" 'flt_compass',\n",
" 'flt_number_of_satelites',\n",
" 'flt_accuracy',\n",
" 'flt_gps_bearing',\n",
" 'flt_obd_engine_load',\n",
" 'flt_obd_engine_rpm',\n",
" 'flt_obd_maf',\n",
" 'flt_obd_accelerator_pedal',\n",
" 'flt_obd_air_temperature',\n",
" 'flt_calc_dist_gps',\n",
" 'flt_calc_dist_vt',\n",
" 'flt_calc_ax_vt',\n",
" 'flt_go_elevation',\n",
" 'flt_go_eleResolution',\n",
" 'flt_distanceIP',\n",
" 'flt_timeIP',\n",
" 'flt_osm_trafficSignal',\n",
" 'flt_osm_w_wood',\n",
" 'flt_join_idx',\n",
" 'flt_curvature',\n",
" 'flt_radius',\n",
" 'flt_phiSegment',\n",
" 'hr_latitude',\n",
" 'hr_longitude',\n",
" 'hr_elevation',\n",
" 'hr_distance',\n",
" 'hr_SpeedLimit',\n",
" 'hr_LinkID',\n",
" 'hr_shapeFirstPoint',\n",
" 'hr_shapeLastPoint',\n",
" 'hr_lengthSegemnt',\n",
" 'hr_remainDistanze',\n",
" 'hr_remainTime',\n",
" 'hr_actualManeuver',\n",
" 'hr_traficSpeed',\n",
" 'hr_traficTime',\n",
" 'hr_baseSpeed',\n",
" 'hr_baseTime',\n",
" 'hr_JamFactor',\n",
" 'hr_FunctionalRoadClass',\n",
" 'hr_consumption',\n",
" 'hr_mTravelTime',\n",
" 'hr_mLenght',\n",
" 'hr_mFirstPoint',\n",
" 'hr_mLastPoint',\n",
" 'hr_mNextManeuver',\n",
" 'hr_mTrafficTime',\n",
" 'hr_mStartAngle',\n",
" 'hr_leg_firtPoint',\n",
" 'hr_leg_lastPoint',\n",
" 'hr_leg_length',\n",
" 'hr_leg_travelTime',\n",
" 'hr_leg_trafficTime',\n",
" 'hr_leg_baseTime',\n",
" 'hr_leg_spot',\n",
" 'hr_leg_shapeIndex',\n",
" 'hr_IdxNP',\n",
" 'hr_NearestPoint_1',\n",
" 'hr_NearestPoint_2',\n",
" 'hr_PointOnRoute_1',\n",
" 'hr_PointOnRoute_2',\n",
" 'hr_Dist2Origin',\n",
" 'hr_Dist2Route',\n",
" 'hr_distance_lldist',\n",
" 'hr_osm_trafficSignal',\n",
" 'hr_osm_w_wood',\n",
" 'hr_distanceIP',\n",
" 'hr_join_idx',\n",
" 'hr_curvature',\n",
" 'hr_radius',\n",
" 'hr_phiSegment',\n",
" 'go_start_latitude',\n",
" 'go_start_longitude',\n",
" 'go_end_latitude',\n",
" 'go_end_longitude',\n",
" 'go_distance',\n",
" 'go_duration',\n",
" 'go_latitude',\n",
" 'go_longitude',\n",
" 'go_routing_flag',\n",
" 'go_mean_velocity_calc_pre',\n",
" 'go_mean_velocity_calc',\n",
" 'go_cum_distance',\n",
" 'go_IdxNP',\n",
" 'go_NearestPoint_1',\n",
" 'go_NearestPoint_2',\n",
" 'go_PointOnRoute_1',\n",
" 'go_PointOnRoute_2',\n",
" 'go_Dist2Origin',\n",
" 'go_Dist2Route',\n",
" 'go_distanceIP',\n",
" 'go_join_idx',\n",
" 'go_curvature',\n",
" 'go_radius',\n",
" 'go_phiSegment',\n",
" 'osrm_latitude',\n",
" 'osrm_longitude',\n",
" 'osrm_seg_datasources',\n",
" 'osrm_seg_weight',\n",
" 'osrm_seg_distance',\n",
" 'osrm_seg_duration',\n",
" 'osrm_seg_nodeID',\n",
" 'osrm_step_weight',\n",
" 'osrm_step_duration',\n",
" 'osrm_step_distance',\n",
" 'osrm_mn_bearing_before',\n",
" 'osrm_mn_bearing_after',\n",
" 'osrm_mn_exit',\n",
" 'osrm_i_lanes_valid_1',\n",
" 'osrm_i_lanes_valid_2',\n",
" 'osrm_i_lanes_valid_3',\n",
" 'osrm_i_lanes_valid_4',\n",
" 'osrm_i_lanes_valid_5',\n",
" 'osrm_i_lanes_valid_6',\n",
" 'osrm_i_bearings_1',\n",
" 'osrm_i_bearings_2',\n",
" 'osrm_i_bearings_3',\n",
" 'osrm_i_bearings_4',\n",
" 'osrm_i_bearings_5',\n",
" 'osrm_i_bearings_6',\n",
" 'osrm_i_entry_1',\n",
" 'osrm_i_entry_2',\n",
" 'osrm_i_entry_3',\n",
" 'osrm_i_entry_4',\n",
" 'osrm_i_entry_5',\n",
" 'osrm_i_entry_6',\n",
" 'osrm_i_in',\n",
" 'osrm_i_out',\n",
" 'osrm_i_laneNumber',\n",
" 'osrm_seg_speed',\n",
" 'osrm_segDistance_lldist',\n",
" 'osrm_seg_cumsumDistance',\n",
" 'osrm_IdxNP',\n",
" 'osrm_NearestPoint_1',\n",
" 'osrm_NearestPoint_2',\n",
" 'osrm_PointOnRoute_1',\n",
" 'osrm_PointOnRoute_2',\n",
" 'osrm_Dist2Origin',\n",
" 'osrm_Dist2Route',\n",
" 'osrm_distanceIP',\n",
" 'osrm_join_idx',\n",
" 'osrm_curvature',\n",
" 'osrm_radius',\n",
" 'osrm_phiSegment',\n",
" 'ors_latitude',\n",
" 'ors_longitude',\n",
" 'ors_elevation',\n",
" 'ors_long_distance',\n",
" 'ors_long_duration',\n",
" 'ors_ascent_route',\n",
" 'ors_descent_route',\n",
" 'ors_detourfactor',\n",
" 'ors_percentage',\n",
" 'ors_avgspeed',\n",
" 'ors_seg_distance',\n",
" 'ors_seg_duration',\n",
" 'ors_type',\n",
" 'ors_maneuver_bearing_before',\n",
" 'ors_maneuver_bearing_after',\n",
" 'ors_seg_speed',\n",
" 'ors_long_speed',\n",
" 'ors_distance_lldist',\n",
" 'ors_seg_distance_cumsum',\n",
" 'ors_long_distance_cumsum',\n",
" 'ors_percentage_cumsum',\n",
" 'ors_IdxNP',\n",
" 'ors_NearestPoint_1',\n",
" 'ors_NearestPoint_2',\n",
" 'ors_PointOnRoute_1',\n",
" 'ors_PointOnRoute_2',\n",
" 'ors_Dist2Origin',\n",
" 'ors_Dist2Route',\n",
" 'ors_distanceIP',\n",
" 'ors_join_idx',\n",
" 'ors_curvature',\n",
" 'ors_radius',\n",
" 'ors_phiSegment',\n",
" 'osm_w_lanes',\n",
" 'osm_w_lanes_forward',\n",
" 'osm_w_lanes_backward',\n",
" 'osm_w_maxspeed',\n",
" 'osm_w_maxspeed_forward',\n",
" 'osm_w_maxspeed_backward',\n",
" 'osm_Node_ID_osrm',\n",
" 'osm_Way_ID',\n",
" 'osm_Way_direction',\n",
" 'osm_Calc_Lanes',\n",
" 'osm_w_maxspeed_new',\n",
" 'osm_latitude',\n",
" 'osm_longitude',\n",
" 'osm_distanceIP',\n",
" 'osm_IdxNP',\n",
" 'osm_NearestPoint_1',\n",
" 'osm_NearestPoint_2',\n",
" 'osm_PointOnRoute_1',\n",
" 'osm_PointOnRoute_2',\n",
" 'osm_Dist2Origin',\n",
" 'osm_Dist2Route',\n",
" 'osm_f_filt',\n",
" 'osm_join_idx',\n",
" 'osm_curvature',\n",
" 'osm_radius',\n",
" 'osm_phiSegment',\n",
" 'tt_latitude',\n",
" 'tt_longitude',\n",
" 'tt_sec_Motorway',\n",
" 'tt_sec_traffic',\n",
" 'tt_calc_speedInKmPerH',\n",
" 'tt_calc_distance',\n",
" 'tt_calc_time',\n",
" 'tt_IdxNP',\n",
" 'tt_NearestPoint_1',\n",
" 'tt_NearestPoint_2',\n",
" 'tt_PointOnRoute_1',\n",
" 'tt_PointOnRoute_2',\n",
" 'tt_Dist2Origin',\n",
" 'tt_Dist2Route',\n",
" 'tt_distanceIP',\n",
" 'tt_join_idx',\n",
" 'tt_curvature',\n",
" 'tt_radius',\n",
" 'tt_phiSegment',\n",
" 'weat_temperature',\n",
" 'weat_precipIntensity',\n",
" 'weat_humidity',\n",
" 'weat_windSpeed',\n",
" 'weat_windBearing',\n",
" 'weat_visibility',\n",
" 'weat_cloudCover',\n",
" 'weat_sunriseTime',\n",
" 'weat_sunsetTime',\n",
" 'weat_latitude',\n",
" 'weat_longitude',\n",
" 'weat_distanceIP',\n",
" 'weat_timeIP',\n",
" 'weat_join_idx',\n",
" 'weat_curvature',\n",
" 'weat_radius',\n",
" 'weat_phiSegment',\n",
" 'mb_latitude',\n",
" 'mb_longitude',\n",
" 'mb_seg_speed',\n",
" 'mb_seg_distance',\n",
" 'mb_seg_duration',\n",
" 'mb_step_weight',\n",
" 'mb_step_duration',\n",
" 'mb_step_distance',\n",
" 'mb_mn_bearing_before',\n",
" 'mb_mn_bearing_after',\n",
" 'mb_mn_exit',\n",
" 'mb_mn_modifier',\n",
" 'mb_i_bearings_1',\n",
" 'mb_i_bearings_2',\n",
" 'mb_i_bearings_3',\n",
" 'mb_i_bearings_4',\n",
" 'mb_i_bearings_5',\n",
" 'mb_i_bearings_6',\n",
" 'mb_i_bearings_7',\n",
" 'mb_i_bearings_8',\n",
" 'mb_i_entry_1',\n",
" 'mb_i_entry_2',\n",
" 'mb_i_entry_3',\n",
" 'mb_i_entry_4',\n",
" 'mb_i_entry_5',\n",
" 'mb_i_entry_6',\n",
" 'mb_i_entry_7',\n",
" 'mb_i_entry_8',\n",
" 'mb_i_in',\n",
" 'mb_i_out',\n",
" 'mb_i_laneNumber',\n",
" 'mb_seg_speed_calc',\n",
" 'mb_segDistance_lldist',\n",
" 'mb_seg_cumsumDistance',\n",
" 'mb_IdxNP',\n",
" 'mb_NearestPoint_1',\n",
" 'mb_NearestPoint_2',\n",
" 'mb_PointOnRoute_1',\n",
" 'mb_PointOnRoute_2',\n",
" 'mb_Dist2Origin',\n",
" 'mb_Dist2Route',\n",
" 'mb_distanceIP',\n",
" 'mb_seg_congestion_calc',\n",
" 'mb_join_idx',\n",
" 'mb_curvature',\n",
" 'mb_radius',\n",
" 'mb_phiSegment',\n",
" 'gh_latitude',\n",
" 'gh_longitude',\n",
" 'gh_elevation',\n",
" 'gh_distance_lldist',\n",
" 'gh_distance',\n",
" 'gh_time',\n",
" 'gh_avgspeed',\n",
" 'gh_sign',\n",
" 'gh_IdxNP',\n",
" 'gh_NearestPoint_1',\n",
" 'gh_NearestPoint_2',\n",
" 'gh_PointOnRoute_1',\n",
" 'gh_PointOnRoute_2',\n",
" 'gh_Dist2Origin',\n",
" 'gh_Dist2Route',\n",
" 'gh_distanceIP',\n",
" 'gh_join_idx',\n",
" 'gh_curvature',\n",
" 'gh_radius',\n",
" 'gh_phiSegment',\n",
" 'mq_latitude',\n",
" 'mq_longitude',\n",
" 'mq_distance_lldist',\n",
" 'mq_distance',\n",
" 'mq_duration',\n",
" 'mq_avgspeed',\n",
" 'mq_avgspeed_leg',\n",
" 'mq_IdxNP',\n",
" 'mq_NearestPoint_1',\n",
" 'mq_NearestPoint_2',\n",
" 'mq_PointOnRoute_1',\n",
" 'mq_PointOnRoute_2',\n",
" 'mq_Dist2Origin',\n",
" 'mq_Dist2Route',\n",
" 'mq_distanceIP',\n",
" 'mq_join_idx',\n",
" 'mq_curvature',\n",
" 'mq_radius',\n",
" 'mq_phiSegment',\n",
" 'bg_latitude',\n",
" 'bg_longitude',\n",
" 'bg_distance',\n",
" 'bg_duration',\n",
" 'bg_avgspeed',\n",
" 'bg_avgspeed_subleg',\n",
" 'bg_avgspeed_leg',\n",
" 'bg_roadShiedType',\n",
" 'bg_distance_lldist',\n",
" 'bg_IdxNP',\n",
" 'bg_NearestPoint_1',\n",
" 'bg_NearestPoint_2',\n",
" 'bg_PointOnRoute_1',\n",
" 'bg_PointOnRoute_2',\n",
" 'bg_Dist2Origin',\n",
" 'bg_Dist2Route',\n",
" 'bg_distanceIP',\n",
" 'bg_join_idx',\n",
" 'bg_curvature',\n",
" 'bg_radius',\n",
" 'bg_phiSegment',\n",
" 'ei_latitude',\n",
" 'ei_longitude',\n",
" 'ei_distance_lldist',\n",
" 'ei_Cumul_Kilometers',\n",
" 'ei_Cumul_TravelTime',\n",
" 'ei_distance',\n",
" 'ei_time',\n",
" 'ei_avgspeed',\n",
" 'ei_IdxNP',\n",
" 'ei_NearestPoint_1',\n",
" 'ei_NearestPoint_2',\n",
" 'ei_PointOnRoute_1',\n",
" 'ei_PointOnRoute_2',\n",
" 'ei_Dist2Origin',\n",
" 'ei_Dist2Route',\n",
" 'ei_distanceIP',\n",
" 'ei_join_idx',\n",
" 'ei_curvature',\n",
" 'ei_radius',\n",
" 'ei_phiSegment',\n",
" 'go_alpha',\n",
" 'hr_alpha',\n",
" 'ors_alpha',\n",
" 'go_alpha_filt',\n",
" 'hr_alpha_filt',\n",
" 'ors_alpha_filt',\n",
" 'hAccel_1',\n",
" 'hAccel_2',\n",
" 'hAccel_3',\n",
" 'flt_mAccel_1',\n",
" 'flt_mAccel_2',\n",
" 'flt_mAccel_3',\n",
" 'flt_mGier_1',\n",
" 'flt_mGier_2',\n",
" 'flt_mGier_3',\n",
" 'rot_Accel_1',\n",
" 'rot_Accel_2',\n",
" 'rot_Accel_3',\n",
" 'rot_Gier_1',\n",
" 'rot_Gier_2',\n",
" 'rot_Gier_3',\n",
" 'rot_Accel_flt_1',\n",
" 'rot_Accel_flt_2',\n",
" 'rot_Accel_flt_3',\n",
" 'rot_Gier_flt_1',\n",
" 'rot_Gier_flt_2',\n",
" 'rot_Gier_flt_3']"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"t.colnames"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"# Calculation ZOOM LEVEL\n",
"width = 640\n",
"height = 640\n",
"tileSize= 256*4\n",
"\n",
"# Converts given lat/lon in WGS84 Datum to XY in Spherical Mercator EPSG:900913\"\n",
"originShift = 2 * math.pi * 6378137/2.0; # 20037508.342789244\n",
"xExtent_min = lon_min * originShift / 180;\n",
"yExtent_min = math.log(math.tan((90 + lat_min) * math.pi / 360 )) / (math.pi / 180);\n",
"yExtent_min = yExtent_min * originShift / 180;\n",
"xExtent_max = lon_max * originShift / 180;\n",
"yExtent_max = math.log(math.tan((90 + lat_max) * math.pi / 360 )) / (math.pi / 180);\n",
"yExtent_max = yExtent_max * originShift / 180;\n",
"\n",
"minResX = (xExtent_max-xExtent_min)/width;\n",
"minResY = (yExtent_max-yExtent_min)/height;\n",
"minRes = max([minResX, minResY]);\n",
"initialResolution = 2 * math.pi * 6378137 / tileSize; # 156543.03392804062 for tileSize 256 pixels\n",
"zoomlevel = math.floor(math.log2(initialResolution/minRes));\n",
"\n",
"# Enforce valid zoom levels\n",
"if zoomlevel < 0:\n",
" zoomlevel = 0\n",
"if zoomlevel > 19: \n",
" zoomlevel = 19"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'\\nfig = go.Figure(go.Scattermapbox(\\n mode = \"markers+lines+text\",\\n lon = Tab[0][1],\\n lat = Tab[0][0],\\n marker = {\\'size\\': 8, \\'color\\':\\'rgb(180,50,50)\\',\\'opacity\\' : 0.25},\\n text=\\'TomTom HCP3 Routing - route shape\\',\\n name=\\'TomTom HCP3 Routing - route shape\\'\\n ))\\nif Tab[i][3] != 0:\\n fig.add_trace(go.Scattermapbox(\\n mode = \"markers+text\",\\n lon = Tab[0][3],\\n lat = Tab[0][2],\\n marker = {\\'size\\':28,\\'color\\':\\'rgb(0,0,200)\\',\\'opacity\\':0.8},\\n text=\\'TomTom HCP3 Routing - charging station\\',\\n name=\\'TomTom HCP3 Routing - charging station\\'\\n ))\\nfig.add_trace(go.Scattermapbox(\\n mode = \"markers\",\\n lon = [str(lng_d)],\\n lat = [str(lat_d)],\\n marker = {\\'size\\': 25, \\'color\\':\\'rgb(180,50,50)\\',\\'opacity\\' : 0.8},\\n text=\\'TomTom HCP3 Routing - destination\\',\\n name=\\'TomTom HCP3 Routing - destination\\'\\n ))\\nfig.add_trace(go.Scattermapbox(\\n mode = \"markers\",\\n lon = [str(lng_s)],\\n lat = [str(lat_s)],\\n marker = {\\'size\\': 25, \\'color\\':\\'rgb(180,50,50)\\',\\'opacity\\' : 0.8},\\n text=\\'TomTom HCP3 Routing - start\\',\\n name=\\'TomTom HCP3 Routing - start\\'\\n ))\\nif select[\\'TT_360Range\\']:\\n try:\\n fig.add_trace(go.Scattermapbox(\\n mode = \"markers+lines+text\",\\n lon = (dfp_r[\\'longitude\\'].astype(float)),\\n lat = (dfp_r[\\'latitude\\'].astype(float)),\\n marker = {\\'size\\': 8, \\'color\\':\\'rgb(180,50,50)\\',\\'opacity\\' : 0.25},\\n text=\\'TomTom HCP3 Routing - range polygon - raw\\',\\n name=\\'TomTom HCP3 Routing - range polygon - raw\\'\\n ))\\n \\n fig.add_trace(go.Scattermapbox(\\n mode = \"markers+lines+text\",\\n lon = (dfp[\\'longitude\\'].astype(float)),\\n lat = (dfp[\\'latitude\\'].astype(float)),\\n marker = {\\'size\\': 8, \\'color\\':\\'rgb(50,180,50)\\',\\'opacity\\' : 0.25},\\n text=\\'TomTom HCP3 Routing - range polygon - detailed\\',\\n name=\\'TomTom HCP3 Routing - range polygon - detailed\\'\\n ))\\n except:\\n print(\"Error fig RangeOnMap \")\\n pass\\nfig.update_layout(\\n margin ={\\'l\\':0,\\'t\\':0,\\'b\\':0,\\'r\\':0},\\n mapbox = {\\n #\\'center\\': {\\'lon\\': lng_s, \\'lat\\': lat_s},\\n \\'style\\': \"stamen-terrain\",\\n \\'center\\': {\\'lon\\': (lng_d+lng_s)/2, \\'lat\\': (lat_d+lat_s)/2},\\n \\'zoom\\': 6})\\n\\nfig.show()\\n'"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import gmplot \n",
"\n",
"######################################\n",
"### Google Plot ###\n",
"######################################\n",
"apikey = 'AIzaSyClu2yvJQjVAQIqs1v6eSEXSgwUNVeDLZM' # (your API key here)\n",
"\n",
"gmap = gmplot.GoogleMapPlotter((lat[0]+lat[-1])/2,\n",
" (lng[0]+lng[-1])/2,\n",
" 7,\n",
" apikey=apikey) \n",
"\n",
"color = ['#B22222','#1E90FF','#C0C0C0','#008000','#BDB76B','#FF8C00','#7FFFD4','#807673','#B22222','#B22222','#1E90FF','#C0C0C0','#008000','#BDB76B','#FF8C00','#7FFFD4','#807673','#B22222','#B22222','#1E90FF','#C0C0C0','#008000','#BDB76B','#FF8C00','#7FFFD4','#807673','#B22222']\n",
"for i in range(1):#len(SETUP_ID)):\n",
" gmap.plot(\n",
" (lat),\n",
" (lng),\n",
" color=color[i],\n",
" edge_width=12-2*i,\n",
" label=('Setup ID: %d' % (SETUP_ID)),\n",
" alpha=1-(i/10)\n",
" )\n",
"'''\n",
" if Tab[i][3] != 0:\n",
" acc_d = 0\n",
" for j in range(len(Tab[i][2])): # iterate through charging stations\n",
" acc_d = acc_d+Tab[i][18][j]/1000\n",
" gmap.marker(\n",
" (Tab[i][2][j]),\n",
" (Tab[i][3][j]),\n",
" color=color[i],\n",
" label=('%d'%(j+1)),\n",
" info_window=('<div id=\"content\">' + '<div id=\"siteNotice\">' + \"</div>\" + '<h1 id=\"firstHeading\" class=\"firstHeading\">' + ('%d - %s Charging' % (j+1,Tab[i][15])) + '</h1>' + '<div id=\"bodyContent\">' + (\"charging time %.2f [min] <br>arrival energy %.2f [kWh] (%.2f %%)<br>target energy %.2f [kWh] (%.2f %%)<br>calculated power %.2f kW <br>Distance of the leg %.2f [km] <br>Acc distance of legs %.2f [km] <br>Charging Name: %s <br>Charging Info: <br> %s\" % (Tab[i][10][j],Tab[i][11][j],Tab[i][11][j]/par['maxChargeInkWh']*100,Tab[i][12][j],Tab[i][12][j]/par['maxChargeInkWh']*100,Tab[i][13][j],Tab[i][18][j]/1000,acc_d,Tab[i][19][j],Tab[i][20][j])) + \"</div>\" + \"</div>\"),\n",
" marker=True,\n",
" title=('%d - %s charging' % (j+1,Tab[i][15])),\n",
" )\n",
"if select['TT_360Range']:\n",
" try:\n",
" gmap.polygon( \n",
" (dfp_r['latitude'].astype(float)),\n",
" (dfp_r['longitude'].astype(float)),\n",
" face_color='#eb8c34', \n",
" edge_color='#73563c',\n",
" edge_width=7,\n",
" label=\"TomTom 360 Range / RangeOnMap - raw\",\n",
" alpha=0.25\n",
" )\n",
" gmap.polygon( \n",
" (dfp['latitude'].astype(float)),\n",
" (dfp['longitude'].astype(float)),\n",
" face_color='#87CEEB', \n",
" edge_color='#3380B3',\n",
" edge_width=7,\n",
" label=\"TomTom 360 Range / RangeOnMap - detailed\",\n",
" alpha=0.5\n",
" )\n",
" except:\n",
" print(\"Error GMap RangeOnMap \")\n",
" pass\n",
"'''\n",
"gmap.marker(\n",
" lat[0],\n",
" lng[0],\n",
" label='S'\n",
" )\n",
"gmap.marker(\n",
" lat[-1], \n",
" lng[-1],\n",
" label='D'\n",
" )\n",
"\n",
" # Pass the absolute path \n",
" #gmap1.draw( \"C:\\\\Users\\\\user\\\\Desktop\\\\map11.html\" ) \n",
" # Draw the map:\n",
"gmap.draw('Routing_onMap.html')\n",
"\n",
"\n",
"##############################################################################################\n",
"\n",
"\n",
"#df,df2 = TomTom_HCP3_Routing(lat_s,lng_s,lat_d,lng_d,cfg,par)\n",
"#TomTom_HCP3\n",
"'''\n",
"fig = go.Figure(go.Scattermapbox(\n",
" mode = \"markers+lines+text\",\n",
" lon = Tab[0][1],\n",
" lat = Tab[0][0],\n",
" marker = {'size': 8, 'color':'rgb(180,50,50)','opacity' : 0.25},\n",
" text='TomTom HCP3 Routing - route shape',\n",
" name='TomTom HCP3 Routing - route shape'\n",
" ))\n",
"if Tab[i][3] != 0:\n",
" fig.add_trace(go.Scattermapbox(\n",
" mode = \"markers+text\",\n",
" lon = Tab[0][3],\n",
" lat = Tab[0][2],\n",
" marker = {'size':28,'color':'rgb(0,0,200)','opacity':0.8},\n",
" text='TomTom HCP3 Routing - charging station',\n",
" name='TomTom HCP3 Routing - charging station'\n",
" ))\n",
"fig.add_trace(go.Scattermapbox(\n",
" mode = \"markers\",\n",
" lon = [str(lng_d)],\n",
" lat = [str(lat_d)],\n",
" marker = {'size': 25, 'color':'rgb(180,50,50)','opacity' : 0.8},\n",
" text='TomTom HCP3 Routing - destination',\n",
" name='TomTom HCP3 Routing - destination'\n",
" ))\n",
"fig.add_trace(go.Scattermapbox(\n",
" mode = \"markers\",\n",
" lon = [str(lng_s)],\n",
" lat = [str(lat_s)],\n",
" marker = {'size': 25, 'color':'rgb(180,50,50)','opacity' : 0.8},\n",
" text='TomTom HCP3 Routing - start',\n",
" name='TomTom HCP3 Routing - start'\n",
" ))\n",
"if select['TT_360Range']:\n",
" try:\n",
" fig.add_trace(go.Scattermapbox(\n",
" mode = \"markers+lines+text\",\n",
" lon = (dfp_r['longitude'].astype(float)),\n",
" lat = (dfp_r['latitude'].astype(float)),\n",
" marker = {'size': 8, 'color':'rgb(180,50,50)','opacity' : 0.25},\n",
" text='TomTom HCP3 Routing - range polygon - raw',\n",
" name='TomTom HCP3 Routing - range polygon - raw'\n",
" ))\n",
" \n",
" fig.add_trace(go.Scattermapbox(\n",
" mode = \"markers+lines+text\",\n",
" lon = (dfp['longitude'].astype(float)),\n",
" lat = (dfp['latitude'].astype(float)),\n",
" marker = {'size': 8, 'color':'rgb(50,180,50)','opacity' : 0.25},\n",
" text='TomTom HCP3 Routing - range polygon - detailed',\n",
" name='TomTom HCP3 Routing - range polygon - detailed'\n",
" ))\n",
" except:\n",
" print(\"Error fig RangeOnMap \")\n",
" pass\n",
"fig.update_layout(\n",
" margin ={'l':0,'t':0,'b':0,'r':0},\n",
" mapbox = {\n",
" #'center': {'lon': lng_s, 'lat': lat_s},\n",
" 'style': \"stamen-terrain\",\n",
" 'center': {'lon': (lng_d+lng_s)/2, 'lat': (lat_d+lat_s)/2},\n",
" 'zoom': 6})\n",
"\n",
"fig.show()\n",
"'''"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
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"/*!\n",
" * The buffer module from node.js, for the browser.\n",
" *\n",
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" * @license MIT\n",
" */\n",
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"/*! Native Promise Only\n",
" v0.8.1 (c) Kyle Simpson\n",
" MIT License: http://getify.mit-license.org\n",
"*/\n",
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],
"source": [
"import plotly.graph_objects as go\n",
"\n",
"\n",
"fig = go.Figure(go.Scattermapbox(\n",
" mode = \"markers+lines+text\",\n",
" lon = lng,\n",
" lat = lat,\n",
" marker = {'size': 8, 'color':'rgb(180,50,50)','opacity' : 0.25},\n",
" text=('Setup ID: %d' % (SETUP_ID)),\n",
" name=('Setup ID: %d' % (SETUP_ID))\n",
" ))\n",
"\n",
"fig.add_trace(go.Scattermapbox(\n",
" mode = \"markers\",\n",
" lon = [str(lng[-1])],\n",
" lat = [str(lat[-1])],\n",
" marker = {'size': 25, 'color':'rgb(180,50,50)','opacity' : 0.8},\n",
" text='destination',\n",
" name='destination'\n",
" ))\n",
"fig.add_trace(go.Scattermapbox(\n",
" mode = \"markers\",\n",
" lon = [str(lng[0])],\n",
" lat = [str(lat[0])],\n",
" marker = {'size': 25, 'color':'rgb(180,50,50)','opacity' : 0.8},\n",
" text='start',\n",
" name='start'\n",
" ))\n",
"\n",
"fig.update_layout(\n",
" margin ={'l':0,'t':0,'b':0,'r':0},\n",
" mapbox = {\n",
" #'center': {'lon': lng_s, 'lat': lat_s},\n",
" 'style': \"stamen-terrain\",\n",
" 'center': {'lon': (lng[-1]+lng[0])/2, 'lat': (lat[-1]+lat[0])/2},\n",
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"\n",
"fig.show()"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"\"\\n# Analyze Data\\n#import plotly\\n#import plotly.graph_objs as go\\n#import plotly.plotly as py\\nimport plotly.graph_objects as go\\nimport plotly.plotly as py\\n\\nplotly.tools.set_credentials_file(username='ziegmann', api_key='yGii8dk78Sjz7jzzad1n')\\nmapbox_access_token = 'pk.eyJ1Ijoiam9oYW5ubmVzLXppZWdtYW5uIiwiYSI6ImNqbDJmamo5bDFxNjQzcWxtd2IzejNhcXoifQ.iVXGH-jpe2FH3f52MM9yHQ'\\n\\ndata_p = [\\n go.Scattermapbox(\\n lat=lat,\\n lon=lng,\\n mode='markers',\\n marker=dict(size=6))\\n]\\n\\nlayout = go.Layout(\\n title='OBD-II GPS Logging',\\n autosize=True,\\n hovermode='closest',\\n mapbox=dict(\\n accesstoken=mapbox_access_token,\\n bearing=0,\\n center=dict(\\n lon=(lon_max-lon_min)/2+lon_min,\\n lat=(lat_max-lat_min)/2+lat_min,\\n ),\\n style='dark',\\n pitch=0,\\n zoom=zoomlevel\\n ),\\n)\\n\\nfig = dict(data=data_p, layout=layout)\\n#plotly.offline.plot(fig, filename='Mapbox.html')\\npy.iplot(fig, filename='Mapbox.html')\\n\\n\""
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"'''\n",
"# Analyze Data\n",
"#import plotly\n",
"#import plotly.graph_objs as go\n",
"#import plotly.plotly as py\n",
"import plotly.graph_objects as go\n",
"import plotly.plotly as py\n",
"\n",
"plotly.tools.set_credentials_file(username='ziegmann', api_key='yGii8dk78Sjz7jzzad1n')\n",
"mapbox_access_token = 'pk.eyJ1Ijoiam9oYW5ubmVzLXppZWdtYW5uIiwiYSI6ImNqbDJmamo5bDFxNjQzcWxtd2IzejNhcXoifQ.iVXGH-jpe2FH3f52MM9yHQ'\n",
"\n",
"data_p = [\n",
" go.Scattermapbox(\n",
" lat=lat,\n",
" lon=lng,\n",
" mode='markers',\n",
" marker=dict(size=6))\n",
"]\n",
"\n",
"layout = go.Layout(\n",
" title='OBD-II GPS Logging',\n",
" autosize=True,\n",
" hovermode='closest',\n",
" mapbox=dict(\n",
" accesstoken=mapbox_access_token,\n",
" bearing=0,\n",
" center=dict(\n",
" lon=(lon_max-lon_min)/2+lon_min,\n",
" lat=(lat_max-lat_min)/2+lat_min,\n",
" ),\n",
" style='dark',\n",
" pitch=0,\n",
" zoom=zoomlevel\n",
" ),\n",
")\n",
"\n",
"fig = dict(data=data_p, layout=layout)\n",
"#plotly.offline.plot(fig, filename='Mapbox.html')\n",
"py.iplot(fig, filename='Mapbox.html')\n",
"\n",
"'''"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.legend.Legend at 0x7fcd77c4bac0>"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 1080x720 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"import matplotlib.pyplot as plot\n",
"temp_d=t['distance']\n",
"xaxis = temp_d # range(int(temp_d[0]), int(temp_d[-1]))\n",
"plot.figure(figsize=(15,10))\n",
"plot.axvline(x=temp_d[TRAINING_RANGE[0]])\n",
"plot.axvline(x=temp_d[TEST_RANGE[0]])\n",
"plot.plot(temp_d[TEST_RANGE[0]:TEST_RANGE[1]], target[TEST_RANGE[0]:TEST_RANGE[1]], 'b',\n",
" xaxis, t['hr_traficSpeed']*3.6, 'r',\n",
" xaxis, t['hr_SpeedLimit'],\n",
" )\n",
"plot.legend(['Training','Test','OBD Speed','HERE Traffic Speed', 'HERE Speed Limint'])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Hyperparametersuche\n",
"\n",
"Utility-Methode; wurde zum Testen verschiedener Ansätze verwendet (könnte man jetzt vermutlich inlinen)"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
"def gridsearch(base, params, n_jobs = None, scoring = 'neg_mean_squared_error', cv = 5):\n",
" if n_jobs == None:\n",
" import os\n",
" n_jobs = os.cpu_count()\n",
" from sklearn.model_selection import GridSearchCV\n",
" return GridSearchCV(base, params, n_jobs = n_jobs, scoring = scoring, cv = cv)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Training\n",
"\n",
"Bei großen Datensätzen kann es zur Fehlerausgabe \"UserWarning: A worker stopped while some jobs were given to the executor. This can be caused by a too short worker timeout or by a memory leak.\" kommen. Scheint vereinzelt am Ergebnis aber nicht viel zu ändern.\n",
"\n",
"Es werden alle gegebenen Parameterkombinationen mittels Cross-Validation getestet; die besten für die Vorhersage verwendet und dann auch ausgegeben."
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning:\n",
"\n",
"`max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
"\n"
]
},
{
"data": {
"text/plain": [
"{'max_depth': 10, 'max_features': 'auto', 'n_estimators': 30}"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from sklearn.ensemble import ExtraTreesRegressor\n",
"clf = gridsearch(ExtraTreesRegressor(),\n",
" [{'n_estimators': range(10, 151, 10), # range(50, 151, 25) woher kommt dieser Range ??? bzw. wie hast du diesen bestimmt\n",
" #'criterion': 'mse', # or mae\n",
" 'max_depth': [None] + list(range(5, 30, 5)), # [None] + list(range(5, 30, 5)) woher kommt die Tiefe???\n",
" 'max_features': ['auto', 'sqrt', 'log2']}])\n",
"clf.fit(data[TRAINING_RANGE[0]:TRAINING_RANGE[1]], target[TRAINING_RANGE[0]:TRAINING_RANGE[1]])\n",
"\n",
"clf.best_params_"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'mean_fit_time': array([ 0.76742554, 1.59367871, 2.40716705, 2.96876788, 3.60309072,\n",
" 4.28540802, 6.41443558, 8.59517479, 10.40094461, 11.78280692,\n",
" 11.96198049, 12.37141967, 13.30578485, 14.33118324, 15.4039238 ,\n",
" 0.0971467 , 0.18501339, 0.27197189, 0.37351727, 0.44626327,\n",
" 0.54063849, 0.62397966, 0.70640478, 0.80144973, 0.89924922,\n",
" 0.9861989 , 1.08484874, 1.17318306, 1.25696516, 1.34836216,\n",
" 0.06538944, 0.12961268, 0.19013028, 0.2449873 , 0.31496029,\n",
" 0.37015281, 0.42959089, 0.48539529, 0.55683017, 0.60459528,\n",
" 0.66702285, 0.74246244, 0.79646344, 0.85169735, 0.93041267,\n",
" 0.45165439, 0.93129153, 1.44718623, 1.8834106 , 2.36375217,\n",
" 2.83906541, 3.27285752, 3.81540036, 4.26078887, 4.65904646,\n",
" 5.20145745, 5.81503711, 6.59189768, 7.31425605, 7.92685132,\n",
" 0.06030006, 0.1277493 , 0.16155777, 0.23977342, 0.24831529,\n",
" 0.29288745, 0.37313361, 0.4231317 , 0.51296096, 0.49702225,\n",
" 0.59252167, 0.62507353, 0.68378577, 0.75570283, 0.89288979,\n",
" 0.04556255, 0.08406444, 0.11632085, 0.14685063, 0.18042641,\n",
" 0.2154984 , 0.25383406, 0.30398922, 0.32567778, 0.36112418,\n",
" 0.48039455, 0.52644672, 0.52096038, 0.51773038, 0.56254635,\n",
" 0.96349216, 1.74700031, 2.70880475, 3.62742443, 4.3028729 ,\n",
" 5.77277036, 6.80227175, 7.26135564, 8.1784349 , 8.6220912 ,\n",
" 10.13566604, 11.06224728, 11.43535333, 12.37456284, 13.60931439,\n",
" 0.09814224, 0.15538816, 0.2159039 , 0.29649816, 0.41454825,\n",
" 0.53023758, 0.497264 , 0.69957666, 0.70203705, 0.86992202,\n",
" 0.79455457, 0.84653654, 0.92664423, 0.97785325, 1.17697105,\n",
" 0.06753793, 0.12679672, 0.14422169, 0.23811879, 0.23826828,\n",
" 0.26836357, 0.31834483, 0.38612328, 0.56462793, 0.6106349 ,\n",
" 0.61000533, 0.63838878, 0.64548755, 0.68801641, 0.82744946,\n",
" 1.28273034, 2.2976233 , 3.19391055, 4.23532619, 5.05803943,\n",
" 6.05001693, 6.99997153, 8.01234241, 9.53076463, 12.02376814,\n",
" 12.36792831, 12.126021 , 13.09200311, 14.13422008, 16.62731056,\n",
" 0.08919706, 0.1698678 , 0.25351162, 0.33951597, 0.49406657,\n",
" 0.6814466 , 0.80368805, 0.8940032 , 1.00371003, 1.0727994 ,\n",
" 1.14241657, 1.31141276, 1.31504812, 1.4657331 , 1.59373441,\n",
" 0.07627368, 0.13848834, 0.19201021, 0.27288852, 0.35024786,\n",
" 0.38515248, 0.48116674, 0.56142673, 0.61736202, 0.73496246,\n",
" 0.77362952, 0.81729612, 0.755093 , 0.90420108, 1.14810071,\n",
" 1.4651566 , 2.60681229, 3.46762018, 4.56561823, 5.61182561,\n",
" 6.78867111, 7.36766567, 8.23273888, 9.22503781, 10.98636432,\n",
" 12.07987528, 12.56972394, 13.31171155, 14.99303727, 16.25762091,\n",
" 0.10615735, 0.19916868, 0.29162807, 0.34974694, 0.48922839,\n",
" 0.53560462, 0.63702908, 0.71479955, 0.81328707, 0.90826068,\n",
" 0.98779678, 1.09777308, 1.2377511 , 1.24945588, 1.35365701,\n",
" 0.06768188, 0.12184019, 0.18550196, 0.24661398, 0.29960589,\n",
" 0.3644762 , 0.43709788, 0.48740253, 0.54465303, 0.61489768,\n",
" 0.68303862, 0.73757834, 0.77604957, 0.83795037, 0.88728266,\n",
" 1.05350041, 2.11901388, 3.14330039, 4.14605684, 5.23948989,\n",
" 6.2884563 , 8.12185059, 10.80232301, 11.63278837, 13.36440754,\n",
" 15.27960968, 17.5897079 , 19.25841675, 20.69372396, 21.49457574,\n",
" 0.12101407, 0.23543725, 0.36546841, 0.46100888, 0.63621306,\n",
" 0.70659566, 0.77198524, 0.87742248, 0.99621396, 1.14121447,\n",
" 1.26780167, 1.38912587, 1.54055686, 1.60529227, 1.77414746,\n",
" 0.08419523, 0.16974587, 0.24338508, 0.30881424, 0.38646231,\n",
" 0.48374453, 0.65572577, 0.72378554, 0.796841 , 0.84118133,\n",
" 0.96884942, 1.21152925, 1.38423066, 1.36233373, 1.21298108]),\n",
" 'std_fit_time': array([0.06464199, 0.05500136, 0.08120297, 0.11348235, 0.16066446,\n",
" 0.41081766, 0.70999249, 0.47763909, 0.60133171, 0.30110774,\n",
" 0.16680913, 0.44446263, 0.65642721, 0.68984789, 0.69413378,\n",
" 0.00325938, 0.00768321, 0.01324165, 0.01380224, 0.02528446,\n",
" 0.01543103, 0.02921876, 0.02508836, 0.02475037, 0.01742597,\n",
" 0.01737943, 0.03182488, 0.06467832, 0.07186308, 0.04486085,\n",
" 0.00343642, 0.00889601, 0.0106354 , 0.01216083, 0.01680061,\n",
" 0.00822477, 0.01733437, 0.01026052, 0.01669627, 0.02853267,\n",
" 0.01927786, 0.03238217, 0.02916449, 0.01556056, 0.05130542,\n",
" 0.01401331, 0.02306618, 0.01774401, 0.07395947, 0.03343157,\n",
" 0.09659112, 0.06380957, 0.12081681, 0.17240564, 0.12484342,\n",
" 0.19623006, 0.22262577, 0.36024329, 0.37212147, 0.31125946,\n",
" 0.00562678, 0.02571752, 0.03049214, 0.03486516, 0.01386237,\n",
" 0.0235969 , 0.03765273, 0.06299097, 0.03998502, 0.02116283,\n",
" 0.03655334, 0.06192981, 0.05820345, 0.06717839, 0.08655225,\n",
" 0.00914498, 0.01410367, 0.01397523, 0.01086611, 0.02239815,\n",
" 0.02345575, 0.0140728 , 0.02545504, 0.03707134, 0.03227538,\n",
" 0.08096537, 0.02978201, 0.02319001, 0.04327471, 0.03824807,\n",
" 0.06756352, 0.1119552 , 0.13415938, 0.21334524, 0.18782295,\n",
" 0.26697412, 0.18110621, 0.27891507, 0.14395822, 0.40127743,\n",
" 0.57754718, 0.37185264, 0.31194259, 0.50714875, 0.28913512,\n",
" 0.02437782, 0.00676064, 0.0120839 , 0.02135435, 0.04677282,\n",
" 0.06161429, 0.01325148, 0.08114917, 0.04769311, 0.04244566,\n",
" 0.01702779, 0.02789691, 0.02763224, 0.01232092, 0.04773943,\n",
" 0.01059273, 0.02297445, 0.00626139, 0.04026825, 0.01115798,\n",
" 0.00318693, 0.00622551, 0.02398376, 0.04361096, 0.06738242,\n",
" 0.04243992, 0.07662459, 0.01791227, 0.100096 , 0.08657557,\n",
" 0.05046906, 0.09480074, 0.12867909, 0.07023567, 0.12424587,\n",
" 0.25048963, 0.37101955, 0.33814325, 0.6200113 , 0.96429621,\n",
" 0.39231427, 0.37292496, 0.48875776, 0.89358708, 1.6282067 ,\n",
" 0.0043924 , 0.00506721, 0.00858216, 0.00915771, 0.0510767 ,\n",
" 0.07115914, 0.09714446, 0.05487629, 0.05602676, 0.08702971,\n",
" 0.09467973, 0.07602358, 0.05188081, 0.09441497, 0.0292244 ,\n",
" 0.0182541 , 0.01769038, 0.03332164, 0.0307917 , 0.0379745 ,\n",
" 0.01679562, 0.01538247, 0.05237519, 0.05585883, 0.02795474,\n",
" 0.03455242, 0.04403889, 0.03789796, 0.04187474, 0.08907306,\n",
" 0.13298527, 0.12253059, 0.10182726, 0.26233453, 0.28685625,\n",
" 0.22673226, 0.21923754, 0.44989556, 0.49433689, 0.78963928,\n",
" 0.36239013, 0.61723021, 0.57097072, 0.89657865, 0.64087246,\n",
" 0.01087369, 0.01935174, 0.02909633, 0.0130759 , 0.03963792,\n",
" 0.02553224, 0.02946354, 0.03532289, 0.03627692, 0.03896694,\n",
" 0.05169964, 0.0659835 , 0.06114282, 0.0602301 , 0.08166079,\n",
" 0.00269181, 0.00347375, 0.00761557, 0.00899742, 0.01479951,\n",
" 0.00912168, 0.01297913, 0.02145531, 0.01849212, 0.05476298,\n",
" 0.02659954, 0.03403707, 0.02177341, 0.02433494, 0.02175655,\n",
" 0.05739407, 0.13464125, 0.17524456, 0.17855824, 0.27682519,\n",
" 0.34395082, 0.79029346, 0.77593114, 0.33810646, 0.64187128,\n",
" 0.93569643, 1.18959621, 0.91120781, 0.80828914, 0.92532714,\n",
" 0.00680129, 0.01251057, 0.03857748, 0.04913605, 0.05646905,\n",
" 0.01578821, 0.03999989, 0.03026651, 0.03942417, 0.05202579,\n",
" 0.04194488, 0.08207969, 0.11158577, 0.08321467, 0.09175438,\n",
" 0.00564495, 0.02376698, 0.02237792, 0.01371333, 0.01883753,\n",
" 0.05260976, 0.0998498 , 0.07089127, 0.06547787, 0.02570303,\n",
" 0.08032804, 0.08028469, 0.10397331, 0.02321052, 0.07423155]),\n",
" 'mean_score_time': array([0.00452852, 0.00484481, 0.00640888, 0.00786819, 0.00826864,\n",
" 0.01181622, 0.01676283, 0.02476449, 0.02182479, 0.02295032,\n",
" 0.02766442, 0.02855144, 0.02865987, 0.03241129, 0.03569822,\n",
" 0.00413156, 0.00590577, 0.00845709, 0.01005473, 0.0121736 ,\n",
" 0.01450925, 0.01726356, 0.01873512, 0.02129636, 0.0234273 ,\n",
" 0.02571497, 0.02863927, 0.03088174, 0.03232265, 0.0366075 ,\n",
" 0.00401688, 0.00688334, 0.00902791, 0.0115706 , 0.01454148,\n",
" 0.01594253, 0.01886983, 0.02117286, 0.02394705, 0.02545257,\n",
" 0.02801614, 0.03051262, 0.03328266, 0.03722401, 0.03856516,\n",
" 0.00397949, 0.00603323, 0.0084074 , 0.01008835, 0.0122479 ,\n",
" 0.01450629, 0.01655335, 0.01905565, 0.02119598, 0.02365971,\n",
" 0.02605529, 0.03902617, 0.03033624, 0.03891091, 0.03838139,\n",
" 0.00556636, 0.0059052 , 0.00818176, 0.01527534, 0.01450849,\n",
" 0.0155643 , 0.02076406, 0.01937737, 0.02954912, 0.02346501,\n",
" 0.02693658, 0.03075662, 0.02928061, 0.03240824, 0.04539824,\n",
" 0.00655251, 0.00663986, 0.0094655 , 0.01324563, 0.01243081,\n",
" 0.01451745, 0.02104278, 0.02288523, 0.02279959, 0.02793698,\n",
" 0.04132662, 0.04381971, 0.03740573, 0.03564205, 0.05376897,\n",
" 0.00391097, 0.00637665, 0.01039014, 0.01055241, 0.0128891 ,\n",
" 0.01533022, 0.01735902, 0.01853957, 0.02138271, 0.02447791,\n",
" 0.02833724, 0.0295856 , 0.02884974, 0.0331306 , 0.04144182,\n",
" 0.00442109, 0.00603709, 0.00816936, 0.01154685, 0.01399469,\n",
" 0.01492615, 0.01637979, 0.02032027, 0.02641864, 0.0274291 ,\n",
" 0.02594638, 0.02922206, 0.03182273, 0.03419614, 0.0488512 ,\n",
" 0.0086772 , 0.00732126, 0.00969324, 0.01254983, 0.01370182,\n",
" 0.01595654, 0.0185102 , 0.02518816, 0.03458214, 0.03299532,\n",
" 0.03889871, 0.03135076, 0.04069605, 0.0464951 , 0.04871435,\n",
" 0.00395889, 0.00632219, 0.00829306, 0.00983591, 0.01225176,\n",
" 0.01531363, 0.01697426, 0.01929808, 0.03214483, 0.03420749,\n",
" 0.02395501, 0.02703891, 0.02860894, 0.03416624, 0.03909421,\n",
" 0.00360737, 0.00566368, 0.00796824, 0.00996113, 0.01391177,\n",
" 0.01898351, 0.02627792, 0.02486043, 0.02421823, 0.02843599,\n",
" 0.0295208 , 0.03675632, 0.02871342, 0.03981647, 0.04354825,\n",
" 0.00642028, 0.00936499, 0.01067781, 0.01357341, 0.01606264,\n",
" 0.01631198, 0.0244185 , 0.02179627, 0.03413568, 0.03639455,\n",
" 0.03411169, 0.03083434, 0.03813024, 0.05278506, 0.0510457 ,\n",
" 0.00713058, 0.00655026, 0.01110525, 0.01072741, 0.01468649,\n",
" 0.01669068, 0.01644249, 0.01851931, 0.02185898, 0.03230128,\n",
" 0.02564864, 0.02621264, 0.02803106, 0.03489313, 0.03623266,\n",
" 0.00402708, 0.00580316, 0.00810432, 0.01428518, 0.01197596,\n",
" 0.0141901 , 0.01687584, 0.01915345, 0.02177095, 0.02415915,\n",
" 0.02594395, 0.03872509, 0.02981634, 0.03281074, 0.03925781,\n",
" 0.00430145, 0.00629382, 0.00910544, 0.0110363 , 0.01362572,\n",
" 0.01550555, 0.0190002 , 0.02094321, 0.02280731, 0.0260191 ,\n",
" 0.02842917, 0.03133187, 0.03222871, 0.03544221, 0.03426471,\n",
" 0.00389962, 0.00828581, 0.00803781, 0.01052713, 0.01265931,\n",
" 0.01505861, 0.02027674, 0.02306232, 0.02556081, 0.02884874,\n",
" 0.03343568, 0.03886037, 0.04013634, 0.0456296 , 0.05673361,\n",
" 0.00459757, 0.00800929, 0.01374063, 0.01519065, 0.01654444,\n",
" 0.01966271, 0.02051907, 0.02412462, 0.02627192, 0.02968884,\n",
" 0.03179197, 0.03642645, 0.03790665, 0.04841967, 0.04666719,\n",
" 0.00544157, 0.00801959, 0.01132307, 0.01423631, 0.0174819 ,\n",
" 0.02188525, 0.03151264, 0.03045154, 0.03928127, 0.0353384 ,\n",
" 0.05195818, 0.05258384, 0.05584388, 0.04835625, 0.03330698]),\n",
" 'std_score_time': array([2.59237298e-03, 6.45427085e-04, 1.45073419e-03, 2.19102585e-03,\n",
" 4.79020423e-04, 3.07619344e-03, 3.92321654e-04, 6.42884078e-03,\n",
" 1.46665951e-03, 9.43327344e-04, 6.13692830e-03, 5.95888777e-04,\n",
" 8.20762009e-04, 2.42232076e-03, 1.90243002e-03, 2.45438651e-04,\n",
" 1.97019258e-04, 8.63356039e-04, 4.15367607e-04, 9.98837812e-04,\n",
" 1.62956529e-03, 1.81588225e-03, 1.20063096e-03, 1.65397105e-03,\n",
" 1.60094317e-03, 1.54078506e-03, 2.60451702e-03, 2.86625530e-03,\n",
" 7.13303014e-04, 2.62682551e-03, 8.95419691e-05, 4.72274875e-04,\n",
" 1.94441506e-04, 6.12734887e-04, 1.04546978e-03, 8.85551763e-04,\n",
" 1.28618828e-03, 9.82161609e-04, 1.59607867e-03, 9.03890628e-04,\n",
" 1.55675056e-03, 1.93951946e-03, 1.32585721e-03, 1.79145842e-03,\n",
" 1.65720272e-03, 1.83890592e-04, 1.98461057e-04, 2.00178113e-04,\n",
" 6.63855127e-04, 4.32578843e-04, 6.75365433e-04, 7.57824192e-04,\n",
" 9.56368876e-04, 9.42283151e-04, 2.19382345e-03, 2.03062911e-03,\n",
" 1.58155789e-02, 2.61689557e-03, 5.47566539e-03, 4.71091840e-03,\n",
" 2.79243356e-03, 1.65348220e-04, 5.53669634e-04, 8.11864174e-03,\n",
" 3.83921501e-03, 2.79202133e-03, 5.92307844e-03, 1.41692493e-03,\n",
" 9.51666604e-03, 5.74148346e-04, 1.65960342e-03, 5.51892849e-03,\n",
" 2.01038082e-03, 3.73316168e-03, 1.29714484e-02, 4.66466905e-03,\n",
" 2.49357778e-04, 1.49415049e-03, 5.78962392e-03, 1.22463233e-03,\n",
" 1.10259600e-03, 5.14647684e-03, 6.49408142e-03, 1.14453145e-03,\n",
" 7.28947606e-03, 1.02327854e-02, 2.70959344e-02, 2.51848590e-03,\n",
" 2.71435640e-03, 1.63370640e-02, 1.71930142e-04, 9.88637413e-04,\n",
" 3.67161322e-03, 1.40868389e-03, 5.55268229e-04, 2.40177951e-03,\n",
" 2.54546248e-03, 8.53011267e-04, 1.22859295e-03, 1.70221014e-03,\n",
" 3.39281125e-03, 3.66692771e-03, 1.73607339e-03, 2.98205206e-03,\n",
" 1.05154773e-02, 9.62234968e-04, 4.00257281e-04, 2.17367065e-04,\n",
" 2.93397155e-03, 1.89571163e-03, 1.30116371e-03, 1.40284748e-03,\n",
" 1.67474297e-03, 8.70760753e-03, 2.99745069e-03, 1.53896226e-03,\n",
" 1.27988421e-03, 1.25922982e-03, 1.78332435e-03, 1.62936380e-02,\n",
" 5.99848469e-03, 1.39219666e-03, 8.33121643e-04, 1.46417829e-03,\n",
" 5.01243945e-04, 3.06031904e-04, 1.16862019e-03, 6.74815879e-03,\n",
" 1.00439949e-02, 4.24354406e-03, 7.86192005e-03, 4.06955446e-03,\n",
" 1.41390802e-02, 1.38915244e-02, 1.04152094e-02, 2.93805427e-04,\n",
" 5.97770133e-04, 8.91939010e-04, 3.23290860e-04, 7.76779565e-04,\n",
" 1.71543857e-03, 1.63105484e-03, 3.87858215e-03, 2.26138982e-02,\n",
" 1.56748038e-02, 1.20432746e-03, 2.85049612e-03, 2.67188894e-03,\n",
" 5.74098505e-03, 3.32468033e-03, 2.24352293e-04, 3.56526535e-04,\n",
" 6.39140072e-04, 3.73455106e-04, 2.55334443e-03, 5.54307661e-03,\n",
" 1.05203601e-02, 3.75591269e-03, 5.52707610e-03, 8.13877237e-03,\n",
" 1.40549719e-03, 7.23507638e-03, 1.00688409e-03, 1.15929885e-02,\n",
" 1.07211797e-02, 3.43232448e-03, 2.69563427e-03, 3.32275498e-03,\n",
" 4.04132272e-03, 4.65152281e-03, 8.13681703e-04, 4.98190994e-03,\n",
" 1.75891474e-03, 1.58136837e-03, 1.92466425e-02, 1.01625998e-02,\n",
" 1.61362984e-03, 5.42831296e-03, 1.39292870e-02, 1.06408163e-02,\n",
" 4.55020529e-03, 1.11092288e-03, 5.80973478e-03, 1.55078864e-03,\n",
" 3.80800197e-03, 3.14153698e-03, 8.58779557e-04, 6.28125258e-04,\n",
" 2.30619833e-03, 1.40704371e-02, 2.12773384e-03, 2.48152370e-04,\n",
" 1.09411799e-03, 2.43377965e-03, 1.70181640e-03, 3.82446867e-04,\n",
" 3.83256287e-04, 9.33432944e-04, 9.05118195e-03, 7.13220696e-04,\n",
" 2.04072355e-04, 4.61010904e-04, 9.64691264e-04, 2.17905565e-03,\n",
" 1.59484581e-03, 1.42743530e-03, 1.72717471e-02, 2.28743439e-03,\n",
" 1.50971173e-03, 8.45731062e-03, 2.99272042e-04, 2.44525582e-04,\n",
" 2.02040130e-04, 4.13281166e-04, 5.04831456e-04, 4.60384041e-04,\n",
" 4.01803107e-04, 1.90224876e-03, 1.14414096e-03, 1.12986574e-03,\n",
" 1.75138067e-03, 1.40746323e-03, 4.21362518e-04, 1.79859250e-03,\n",
" 1.76554585e-03, 2.63390422e-04, 3.83895076e-03, 7.30524969e-04,\n",
" 1.05309113e-03, 8.10915544e-04, 4.53370155e-04, 4.54575603e-04,\n",
" 6.73626718e-04, 8.02536662e-04, 1.18332082e-03, 2.11734666e-03,\n",
" 8.97299490e-03, 7.24847150e-03, 8.13302938e-03, 2.66808475e-02,\n",
" 1.11229011e-04, 1.32900452e-03, 4.64371457e-03, 4.15856877e-03,\n",
" 1.90272014e-03, 2.44008302e-03, 4.34243570e-04, 2.82202777e-03,\n",
" 1.21127245e-03, 1.83141329e-03, 1.52463602e-03, 2.66730123e-03,\n",
" 9.07645759e-04, 1.53912160e-02, 1.50172233e-03, 4.40142410e-04,\n",
" 2.34275080e-04, 5.76509191e-04, 7.45278976e-04, 8.04067831e-04,\n",
" 1.52569633e-03, 5.17490695e-03, 6.68139254e-03, 1.21261966e-02,\n",
" 4.83483683e-03, 1.00024555e-02, 1.03115818e-02, 1.43492817e-02,\n",
" 8.09002546e-03, 1.04912226e-02]),\n",
" 'param_max_depth': masked_array(data=[None, None, None, None, None, None, None, None, None,\n",
" None, None, None, None, None, None, None, None, None,\n",
" None, None, None, None, None, None, None, None, None,\n",
" None, None, None, None, None, None, None, None, None,\n",
" None, None, None, None, None, None, None, None, None,\n",
" 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5,\n",
" 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5,\n",
" 5, 5, 5, 5, 5, 5, 5, 5, 5, 10, 10, 10, 10, 10, 10, 10,\n",
" 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10,\n",
" 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10,\n",
" 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 15, 15, 15, 15,\n",
" 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15,\n",
" 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15,\n",
" 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 20,\n",
" 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20,\n",
" 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20,\n",
" 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20,\n",
" 20, 20, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25,\n",
" 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25,\n",
" 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25,\n",
" 25, 25, 25, 25, 25],\n",
" mask=[False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False],\n",
" fill_value='?',\n",
" dtype=object),\n",
" 'param_max_features': masked_array(data=['auto', 'auto', 'auto', 'auto', 'auto', 'auto', 'auto',\n",
" 'auto', 'auto', 'auto', 'auto', 'auto', 'auto', 'auto',\n",
" 'auto', 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'sqrt',\n",
" 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'sqrt',\n",
" 'sqrt', 'sqrt', 'log2', 'log2', 'log2', 'log2', 'log2',\n",
" 'log2', 'log2', 'log2', 'log2', 'log2', 'log2', 'log2',\n",
" 'log2', 'log2', 'log2', 'auto', 'auto', 'auto', 'auto',\n",
" 'auto', 'auto', 'auto', 'auto', 'auto', 'auto', 'auto',\n",
" 'auto', 'auto', 'auto', 'auto', 'sqrt', 'sqrt', 'sqrt',\n",
" 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'sqrt',\n",
" 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'log2', 'log2',\n",
" 'log2', 'log2', 'log2', 'log2', 'log2', 'log2', 'log2',\n",
" 'log2', 'log2', 'log2', 'log2', 'log2', 'log2', 'auto',\n",
" 'auto', 'auto', 'auto', 'auto', 'auto', 'auto', 'auto',\n",
" 'auto', 'auto', 'auto', 'auto', 'auto', 'auto', 'auto',\n",
" 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'sqrt',\n",
" 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'sqrt',\n",
" 'sqrt', 'log2', 'log2', 'log2', 'log2', 'log2', 'log2',\n",
" 'log2', 'log2', 'log2', 'log2', 'log2', 'log2', 'log2',\n",
" 'log2', 'log2', 'auto', 'auto', 'auto', 'auto', 'auto',\n",
" 'auto', 'auto', 'auto', 'auto', 'auto', 'auto', 'auto',\n",
" 'auto', 'auto', 'auto', 'sqrt', 'sqrt', 'sqrt', 'sqrt',\n",
" 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'sqrt',\n",
" 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'log2', 'log2', 'log2',\n",
" 'log2', 'log2', 'log2', 'log2', 'log2', 'log2', 'log2',\n",
" 'log2', 'log2', 'log2', 'log2', 'log2', 'auto', 'auto',\n",
" 'auto', 'auto', 'auto', 'auto', 'auto', 'auto', 'auto',\n",
" 'auto', 'auto', 'auto', 'auto', 'auto', 'auto', 'sqrt',\n",
" 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'sqrt',\n",
" 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'sqrt',\n",
" 'log2', 'log2', 'log2', 'log2', 'log2', 'log2', 'log2',\n",
" 'log2', 'log2', 'log2', 'log2', 'log2', 'log2', 'log2',\n",
" 'log2', 'auto', 'auto', 'auto', 'auto', 'auto', 'auto',\n",
" 'auto', 'auto', 'auto', 'auto', 'auto', 'auto', 'auto',\n",
" 'auto', 'auto', 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'sqrt',\n",
" 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'sqrt',\n",
" 'sqrt', 'sqrt', 'sqrt', 'log2', 'log2', 'log2', 'log2',\n",
" 'log2', 'log2', 'log2', 'log2', 'log2', 'log2', 'log2',\n",
" 'log2', 'log2', 'log2', 'log2'],\n",
" mask=[False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False],\n",
" fill_value='?',\n",
" dtype=object),\n",
" 'param_n_estimators': masked_array(data=[10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, 120, 130,\n",
" 140, 150, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110,\n",
" 120, 130, 140, 150, 10, 20, 30, 40, 50, 60, 70, 80, 90,\n",
" 100, 110, 120, 130, 140, 150, 10, 20, 30, 40, 50, 60,\n",
" 70, 80, 90, 100, 110, 120, 130, 140, 150, 10, 20, 30,\n",
" 40, 50, 60, 70, 80, 90, 100, 110, 120, 130, 140, 150,\n",
" 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, 120, 130,\n",
" 140, 150, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110,\n",
" 120, 130, 140, 150, 10, 20, 30, 40, 50, 60, 70, 80, 90,\n",
" 100, 110, 120, 130, 140, 150, 10, 20, 30, 40, 50, 60,\n",
" 70, 80, 90, 100, 110, 120, 130, 140, 150, 10, 20, 30,\n",
" 40, 50, 60, 70, 80, 90, 100, 110, 120, 130, 140, 150,\n",
" 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, 120, 130,\n",
" 140, 150, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110,\n",
" 120, 130, 140, 150, 10, 20, 30, 40, 50, 60, 70, 80, 90,\n",
" 100, 110, 120, 130, 140, 150, 10, 20, 30, 40, 50, 60,\n",
" 70, 80, 90, 100, 110, 120, 130, 140, 150, 10, 20, 30,\n",
" 40, 50, 60, 70, 80, 90, 100, 110, 120, 130, 140, 150,\n",
" 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, 120, 130,\n",
" 140, 150, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110,\n",
" 120, 130, 140, 150, 10, 20, 30, 40, 50, 60, 70, 80, 90,\n",
" 100, 110, 120, 130, 140, 150],\n",
" mask=[False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False],\n",
" fill_value='?',\n",
" dtype=object),\n",
" 'params': [{'max_depth': None, 'max_features': 'auto', 'n_estimators': 10},\n",
" {'max_depth': None, 'max_features': 'auto', 'n_estimators': 20},\n",
" {'max_depth': None, 'max_features': 'auto', 'n_estimators': 30},\n",
" {'max_depth': None, 'max_features': 'auto', 'n_estimators': 40},\n",
" {'max_depth': None, 'max_features': 'auto', 'n_estimators': 50},\n",
" {'max_depth': None, 'max_features': 'auto', 'n_estimators': 60},\n",
" {'max_depth': None, 'max_features': 'auto', 'n_estimators': 70},\n",
" {'max_depth': None, 'max_features': 'auto', 'n_estimators': 80},\n",
" {'max_depth': None, 'max_features': 'auto', 'n_estimators': 90},\n",
" {'max_depth': None, 'max_features': 'auto', 'n_estimators': 100},\n",
" {'max_depth': None, 'max_features': 'auto', 'n_estimators': 110},\n",
" {'max_depth': None, 'max_features': 'auto', 'n_estimators': 120},\n",
" {'max_depth': None, 'max_features': 'auto', 'n_estimators': 130},\n",
" {'max_depth': None, 'max_features': 'auto', 'n_estimators': 140},\n",
" {'max_depth': None, 'max_features': 'auto', 'n_estimators': 150},\n",
" {'max_depth': None, 'max_features': 'sqrt', 'n_estimators': 10},\n",
" {'max_depth': None, 'max_features': 'sqrt', 'n_estimators': 20},\n",
" {'max_depth': None, 'max_features': 'sqrt', 'n_estimators': 30},\n",
" {'max_depth': None, 'max_features': 'sqrt', 'n_estimators': 40},\n",
" {'max_depth': None, 'max_features': 'sqrt', 'n_estimators': 50},\n",
" {'max_depth': None, 'max_features': 'sqrt', 'n_estimators': 60},\n",
" {'max_depth': None, 'max_features': 'sqrt', 'n_estimators': 70},\n",
" {'max_depth': None, 'max_features': 'sqrt', 'n_estimators': 80},\n",
" {'max_depth': None, 'max_features': 'sqrt', 'n_estimators': 90},\n",
" {'max_depth': None, 'max_features': 'sqrt', 'n_estimators': 100},\n",
" {'max_depth': None, 'max_features': 'sqrt', 'n_estimators': 110},\n",
" {'max_depth': None, 'max_features': 'sqrt', 'n_estimators': 120},\n",
" {'max_depth': None, 'max_features': 'sqrt', 'n_estimators': 130},\n",
" {'max_depth': None, 'max_features': 'sqrt', 'n_estimators': 140},\n",
" {'max_depth': None, 'max_features': 'sqrt', 'n_estimators': 150},\n",
" {'max_depth': None, 'max_features': 'log2', 'n_estimators': 10},\n",
" {'max_depth': None, 'max_features': 'log2', 'n_estimators': 20},\n",
" {'max_depth': None, 'max_features': 'log2', 'n_estimators': 30},\n",
" {'max_depth': None, 'max_features': 'log2', 'n_estimators': 40},\n",
" {'max_depth': None, 'max_features': 'log2', 'n_estimators': 50},\n",
" {'max_depth': None, 'max_features': 'log2', 'n_estimators': 60},\n",
" {'max_depth': None, 'max_features': 'log2', 'n_estimators': 70},\n",
" {'max_depth': None, 'max_features': 'log2', 'n_estimators': 80},\n",
" {'max_depth': None, 'max_features': 'log2', 'n_estimators': 90},\n",
" {'max_depth': None, 'max_features': 'log2', 'n_estimators': 100},\n",
" {'max_depth': None, 'max_features': 'log2', 'n_estimators': 110},\n",
" {'max_depth': None, 'max_features': 'log2', 'n_estimators': 120},\n",
" {'max_depth': None, 'max_features': 'log2', 'n_estimators': 130},\n",
" {'max_depth': None, 'max_features': 'log2', 'n_estimators': 140},\n",
" {'max_depth': None, 'max_features': 'log2', 'n_estimators': 150},\n",
" {'max_depth': 5, 'max_features': 'auto', 'n_estimators': 10},\n",
" {'max_depth': 5, 'max_features': 'auto', 'n_estimators': 20},\n",
" {'max_depth': 5, 'max_features': 'auto', 'n_estimators': 30},\n",
" {'max_depth': 5, 'max_features': 'auto', 'n_estimators': 40},\n",
" {'max_depth': 5, 'max_features': 'auto', 'n_estimators': 50},\n",
" {'max_depth': 5, 'max_features': 'auto', 'n_estimators': 60},\n",
" {'max_depth': 5, 'max_features': 'auto', 'n_estimators': 70},\n",
" {'max_depth': 5, 'max_features': 'auto', 'n_estimators': 80},\n",
" {'max_depth': 5, 'max_features': 'auto', 'n_estimators': 90},\n",
" {'max_depth': 5, 'max_features': 'auto', 'n_estimators': 100},\n",
" {'max_depth': 5, 'max_features': 'auto', 'n_estimators': 110},\n",
" {'max_depth': 5, 'max_features': 'auto', 'n_estimators': 120},\n",
" {'max_depth': 5, 'max_features': 'auto', 'n_estimators': 130},\n",
" {'max_depth': 5, 'max_features': 'auto', 'n_estimators': 140},\n",
" {'max_depth': 5, 'max_features': 'auto', 'n_estimators': 150},\n",
" {'max_depth': 5, 'max_features': 'sqrt', 'n_estimators': 10},\n",
" {'max_depth': 5, 'max_features': 'sqrt', 'n_estimators': 20},\n",
" {'max_depth': 5, 'max_features': 'sqrt', 'n_estimators': 30},\n",
" {'max_depth': 5, 'max_features': 'sqrt', 'n_estimators': 40},\n",
" {'max_depth': 5, 'max_features': 'sqrt', 'n_estimators': 50},\n",
" {'max_depth': 5, 'max_features': 'sqrt', 'n_estimators': 60},\n",
" {'max_depth': 5, 'max_features': 'sqrt', 'n_estimators': 70},\n",
" {'max_depth': 5, 'max_features': 'sqrt', 'n_estimators': 80},\n",
" {'max_depth': 5, 'max_features': 'sqrt', 'n_estimators': 90},\n",
" {'max_depth': 5, 'max_features': 'sqrt', 'n_estimators': 100},\n",
" {'max_depth': 5, 'max_features': 'sqrt', 'n_estimators': 110},\n",
" {'max_depth': 5, 'max_features': 'sqrt', 'n_estimators': 120},\n",
" {'max_depth': 5, 'max_features': 'sqrt', 'n_estimators': 130},\n",
" {'max_depth': 5, 'max_features': 'sqrt', 'n_estimators': 140},\n",
" {'max_depth': 5, 'max_features': 'sqrt', 'n_estimators': 150},\n",
" {'max_depth': 5, 'max_features': 'log2', 'n_estimators': 10},\n",
" {'max_depth': 5, 'max_features': 'log2', 'n_estimators': 20},\n",
" {'max_depth': 5, 'max_features': 'log2', 'n_estimators': 30},\n",
" {'max_depth': 5, 'max_features': 'log2', 'n_estimators': 40},\n",
" {'max_depth': 5, 'max_features': 'log2', 'n_estimators': 50},\n",
" {'max_depth': 5, 'max_features': 'log2', 'n_estimators': 60},\n",
" {'max_depth': 5, 'max_features': 'log2', 'n_estimators': 70},\n",
" {'max_depth': 5, 'max_features': 'log2', 'n_estimators': 80},\n",
" {'max_depth': 5, 'max_features': 'log2', 'n_estimators': 90},\n",
" {'max_depth': 5, 'max_features': 'log2', 'n_estimators': 100},\n",
" {'max_depth': 5, 'max_features': 'log2', 'n_estimators': 110},\n",
" {'max_depth': 5, 'max_features': 'log2', 'n_estimators': 120},\n",
" {'max_depth': 5, 'max_features': 'log2', 'n_estimators': 130},\n",
" {'max_depth': 5, 'max_features': 'log2', 'n_estimators': 140},\n",
" {'max_depth': 5, 'max_features': 'log2', 'n_estimators': 150},\n",
" {'max_depth': 10, 'max_features': 'auto', 'n_estimators': 10},\n",
" {'max_depth': 10, 'max_features': 'auto', 'n_estimators': 20},\n",
" {'max_depth': 10, 'max_features': 'auto', 'n_estimators': 30},\n",
" {'max_depth': 10, 'max_features': 'auto', 'n_estimators': 40},\n",
" {'max_depth': 10, 'max_features': 'auto', 'n_estimators': 50},\n",
" {'max_depth': 10, 'max_features': 'auto', 'n_estimators': 60},\n",
" {'max_depth': 10, 'max_features': 'auto', 'n_estimators': 70},\n",
" {'max_depth': 10, 'max_features': 'auto', 'n_estimators': 80},\n",
" {'max_depth': 10, 'max_features': 'auto', 'n_estimators': 90},\n",
" {'max_depth': 10, 'max_features': 'auto', 'n_estimators': 100},\n",
" {'max_depth': 10, 'max_features': 'auto', 'n_estimators': 110},\n",
" {'max_depth': 10, 'max_features': 'auto', 'n_estimators': 120},\n",
" {'max_depth': 10, 'max_features': 'auto', 'n_estimators': 130},\n",
" {'max_depth': 10, 'max_features': 'auto', 'n_estimators': 140},\n",
" {'max_depth': 10, 'max_features': 'auto', 'n_estimators': 150},\n",
" {'max_depth': 10, 'max_features': 'sqrt', 'n_estimators': 10},\n",
" {'max_depth': 10, 'max_features': 'sqrt', 'n_estimators': 20},\n",
" {'max_depth': 10, 'max_features': 'sqrt', 'n_estimators': 30},\n",
" {'max_depth': 10, 'max_features': 'sqrt', 'n_estimators': 40},\n",
" {'max_depth': 10, 'max_features': 'sqrt', 'n_estimators': 50},\n",
" {'max_depth': 10, 'max_features': 'sqrt', 'n_estimators': 60},\n",
" {'max_depth': 10, 'max_features': 'sqrt', 'n_estimators': 70},\n",
" {'max_depth': 10, 'max_features': 'sqrt', 'n_estimators': 80},\n",
" {'max_depth': 10, 'max_features': 'sqrt', 'n_estimators': 90},\n",
" {'max_depth': 10, 'max_features': 'sqrt', 'n_estimators': 100},\n",
" {'max_depth': 10, 'max_features': 'sqrt', 'n_estimators': 110},\n",
" {'max_depth': 10, 'max_features': 'sqrt', 'n_estimators': 120},\n",
" {'max_depth': 10, 'max_features': 'sqrt', 'n_estimators': 130},\n",
" {'max_depth': 10, 'max_features': 'sqrt', 'n_estimators': 140},\n",
" {'max_depth': 10, 'max_features': 'sqrt', 'n_estimators': 150},\n",
" {'max_depth': 10, 'max_features': 'log2', 'n_estimators': 10},\n",
" {'max_depth': 10, 'max_features': 'log2', 'n_estimators': 20},\n",
" {'max_depth': 10, 'max_features': 'log2', 'n_estimators': 30},\n",
" {'max_depth': 10, 'max_features': 'log2', 'n_estimators': 40},\n",
" {'max_depth': 10, 'max_features': 'log2', 'n_estimators': 50},\n",
" {'max_depth': 10, 'max_features': 'log2', 'n_estimators': 60},\n",
" {'max_depth': 10, 'max_features': 'log2', 'n_estimators': 70},\n",
" {'max_depth': 10, 'max_features': 'log2', 'n_estimators': 80},\n",
" {'max_depth': 10, 'max_features': 'log2', 'n_estimators': 90},\n",
" {'max_depth': 10, 'max_features': 'log2', 'n_estimators': 100},\n",
" {'max_depth': 10, 'max_features': 'log2', 'n_estimators': 110},\n",
" {'max_depth': 10, 'max_features': 'log2', 'n_estimators': 120},\n",
" {'max_depth': 10, 'max_features': 'log2', 'n_estimators': 130},\n",
" {'max_depth': 10, 'max_features': 'log2', 'n_estimators': 140},\n",
" {'max_depth': 10, 'max_features': 'log2', 'n_estimators': 150},\n",
" {'max_depth': 15, 'max_features': 'auto', 'n_estimators': 10},\n",
" {'max_depth': 15, 'max_features': 'auto', 'n_estimators': 20},\n",
" {'max_depth': 15, 'max_features': 'auto', 'n_estimators': 30},\n",
" {'max_depth': 15, 'max_features': 'auto', 'n_estimators': 40},\n",
" {'max_depth': 15, 'max_features': 'auto', 'n_estimators': 50},\n",
" {'max_depth': 15, 'max_features': 'auto', 'n_estimators': 60},\n",
" {'max_depth': 15, 'max_features': 'auto', 'n_estimators': 70},\n",
" {'max_depth': 15, 'max_features': 'auto', 'n_estimators': 80},\n",
" {'max_depth': 15, 'max_features': 'auto', 'n_estimators': 90},\n",
" {'max_depth': 15, 'max_features': 'auto', 'n_estimators': 100},\n",
" {'max_depth': 15, 'max_features': 'auto', 'n_estimators': 110},\n",
" {'max_depth': 15, 'max_features': 'auto', 'n_estimators': 120},\n",
" {'max_depth': 15, 'max_features': 'auto', 'n_estimators': 130},\n",
" {'max_depth': 15, 'max_features': 'auto', 'n_estimators': 140},\n",
" {'max_depth': 15, 'max_features': 'auto', 'n_estimators': 150},\n",
" {'max_depth': 15, 'max_features': 'sqrt', 'n_estimators': 10},\n",
" {'max_depth': 15, 'max_features': 'sqrt', 'n_estimators': 20},\n",
" {'max_depth': 15, 'max_features': 'sqrt', 'n_estimators': 30},\n",
" {'max_depth': 15, 'max_features': 'sqrt', 'n_estimators': 40},\n",
" {'max_depth': 15, 'max_features': 'sqrt', 'n_estimators': 50},\n",
" {'max_depth': 15, 'max_features': 'sqrt', 'n_estimators': 60},\n",
" {'max_depth': 15, 'max_features': 'sqrt', 'n_estimators': 70},\n",
" {'max_depth': 15, 'max_features': 'sqrt', 'n_estimators': 80},\n",
" {'max_depth': 15, 'max_features': 'sqrt', 'n_estimators': 90},\n",
" {'max_depth': 15, 'max_features': 'sqrt', 'n_estimators': 100},\n",
" {'max_depth': 15, 'max_features': 'sqrt', 'n_estimators': 110},\n",
" {'max_depth': 15, 'max_features': 'sqrt', 'n_estimators': 120},\n",
" {'max_depth': 15, 'max_features': 'sqrt', 'n_estimators': 130},\n",
" {'max_depth': 15, 'max_features': 'sqrt', 'n_estimators': 140},\n",
" {'max_depth': 15, 'max_features': 'sqrt', 'n_estimators': 150},\n",
" {'max_depth': 15, 'max_features': 'log2', 'n_estimators': 10},\n",
" {'max_depth': 15, 'max_features': 'log2', 'n_estimators': 20},\n",
" {'max_depth': 15, 'max_features': 'log2', 'n_estimators': 30},\n",
" {'max_depth': 15, 'max_features': 'log2', 'n_estimators': 40},\n",
" {'max_depth': 15, 'max_features': 'log2', 'n_estimators': 50},\n",
" {'max_depth': 15, 'max_features': 'log2', 'n_estimators': 60},\n",
" {'max_depth': 15, 'max_features': 'log2', 'n_estimators': 70},\n",
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" -65.26881118, -63.0833519 , -70.36142164, -67.48967147,\n",
" -60.47843468, -62.01070472, -62.76699149, -103.7018652 ,\n",
" -104.33722105, -98.50045598, -83.85731836, -101.39585578,\n",
" -88.10203058, -110.20443127, -99.56615351, -97.05821582,\n",
" -106.18887316, -100.55008858, -95.76888364, -97.44792468,\n",
" -94.92259854, -97.57154645, -176.24189787, -108.71631258,\n",
" -104.32452024, -106.38462895, -108.64477169, -111.95962394,\n",
" -108.06193376, -104.19128495, -106.16195949, -107.52565128,\n",
" -110.69745518, -112.09446519, -108.60676599, -98.15267498,\n",
" -109.72691357, -89.88605538, -59.97249703, -61.90321004,\n",
" -58.39825219, -63.10784319, -66.81117578, -70.71464804,\n",
" -68.64080563, -61.79611956, -66.82344998, -66.4420607 ,\n",
" -67.96016555, -57.75076535, -61.75538283, -61.91239469,\n",
" -112.67387916, -102.06776738, -121.52677964, -97.21329518,\n",
" -96.12221191, -93.53686706, -100.16553792, -103.21046154,\n",
" -96.4669859 , -100.27058916, -101.47066532, -105.20401702,\n",
" -99.4927585 , -94.13806222, -91.41590889, -110.47800011,\n",
" -127.4129971 , -105.09300791, -115.32228291, -97.50640525,\n",
" -99.41051875, -111.43688773, -109.27572187, -107.48301403,\n",
" -108.06355337, -109.95080828, -102.36112748, -106.80374602,\n",
" -108.9489739 , -105.58510313]),\n",
" 'std_test_score': array([ 58.26811574, 40.93420876, 42.57889031, 38.51244443,\n",
" 48.95357673, 38.00484638, 39.67837451, 41.52699034,\n",
" 49.65886433, 47.44017477, 44.80208713, 43.74924395,\n",
" 40.58362298, 39.57851723, 45.84472225, 53.67272192,\n",
" 74.93858955, 70.79862048, 66.58062834, 73.17575679,\n",
" 66.66646476, 70.38796144, 70.16157004, 72.9450207 ,\n",
" 65.29167556, 69.30706184, 67.91867528, 65.35232853,\n",
" 65.3531261 , 65.86861222, 76.88029229, 66.52756156,\n",
" 62.57921511, 55.53653269, 64.03469382, 61.27185536,\n",
" 54.7563661 , 69.83002197, 58.7694582 , 58.73637809,\n",
" 62.97690923, 67.39087495, 66.3327575 , 64.30052518,\n",
" 62.44060789, 103.80752078, 41.42195137, 36.62377723,\n",
" 48.86255527, 44.16236338, 41.64734721, 49.73866077,\n",
" 44.25780204, 46.16832373, 47.98773465, 47.99543365,\n",
" 48.22569061, 41.85795609, 45.47384508, 40.96599778,\n",
" 113.23991744, 53.76670302, 47.3650498 , 60.60883634,\n",
" 67.30180038, 50.56242995, 58.78921486, 74.44886876,\n",
" 59.36675839, 61.81265661, 64.23261225, 61.47776005,\n",
" 62.81987789, 66.53775094, 62.91728543, 78.82408106,\n",
" 75.97784543, 53.35222432, 69.10029803, 59.82189466,\n",
" 62.64297289, 63.75442876, 60.98606489, 69.27634713,\n",
" 68.27017422, 58.14211156, 60.01418728, 60.52424608,\n",
" 55.54841089, 55.95218315, 51.14649682, 47.5750827 ,\n",
" 36.71371784, 45.90410866, 39.49289594, 42.59720693,\n",
" 44.20235059, 40.73817023, 45.08137971, 41.84196781,\n",
" 43.39261309, 39.93783136, 47.03432351, 40.57991648,\n",
" 38.07764638, 53.77870351, 67.00039132, 68.42655287,\n",
" 71.0995293 , 72.48058599, 68.82307614, 57.05902698,\n",
" 68.40543877, 66.2110123 , 64.43862163, 73.20833086,\n",
" 69.86813384, 69.30081947, 66.99651661, 65.8552435 ,\n",
" 50.94899544, 55.1208268 , 71.43106681, 61.99320823,\n",
" 66.24971252, 68.60057495, 66.12459282, 55.11930868,\n",
" 63.22848927, 57.7677251 , 57.99557999, 66.15253292,\n",
" 60.80639378, 66.53747929, 61.68451872, 43.10091921,\n",
" 35.38442127, 40.06821297, 40.01534853, 42.08412901,\n",
" 41.35221124, 44.5199146 , 40.13053996, 48.09764459,\n",
" 46.65112227, 38.17403951, 41.84834514, 38.70945631,\n",
" 41.66711279, 41.77351106, 56.04418303, 69.77111058,\n",
" 56.80102631, 66.42403535, 55.33170042, 68.59177371,\n",
" 70.32367995, 61.80456625, 67.77483752, 67.21797309,\n",
" 66.86025118, 64.83020352, 71.61950429, 66.43454956,\n",
" 68.12388434, 41.50061811, 66.23260431, 69.35127096,\n",
" 73.34949483, 66.74830825, 62.87498967, 61.57916396,\n",
" 64.36250339, 61.70237329, 69.07709755, 65.49916847,\n",
" 61.53121861, 62.99314833, 68.11929812, 63.92123018,\n",
" 46.79987315, 38.16453198, 50.6240174 , 42.93082267,\n",
" 48.11852145, 44.41605485, 43.54897353, 43.62902036,\n",
" 43.71739788, 45.94561797, 48.1557157 , 43.55945253,\n",
" 40.03655983, 39.43689889, 45.2446645 , 74.45607523,\n",
" 78.43266925, 71.53667576, 64.79494311, 70.58138849,\n",
" 65.29166495, 77.71293101, 69.53292732, 67.12030653,\n",
" 72.64108811, 65.12792828, 66.30007516, 68.26781999,\n",
" 67.68260354, 71.97054944, 81.49961378, 68.50320821,\n",
" 66.0496272 , 69.24986739, 62.44569276, 64.4350026 ,\n",
" 61.43599146, 63.48800204, 66.73919761, 67.78376561,\n",
" 62.12482145, 59.54229732, 64.24007293, 66.91524515,\n",
" 68.86116965, 66.7497161 , 42.61686792, 47.56261132,\n",
" 44.41754577, 42.88799312, 43.47303828, 48.2944551 ,\n",
" 44.01055203, 41.95880797, 43.71595797, 44.04196032,\n",
" 49.17892961, 39.4711381 , 42.2245005 , 39.92212829,\n",
" 54.97385521, 80.54413074, 74.25304011, 68.05462511,\n",
" 69.98317156, 73.85500425, 65.13383818, 62.85791124,\n",
" 64.26307064, 61.86586373, 73.19491545, 61.87066544,\n",
" 74.33610377, 64.65603795, 71.77833228, 71.77267501,\n",
" 45.65033847, 57.90806333, 63.3248382 , 67.90977292,\n",
" 72.42420185, 62.78323642, 60.14690679, 61.38139799,\n",
" 63.09400312, 58.18294885, 64.3408189 , 71.45269433,\n",
" 64.97846643, 68.44704176]),\n",
" 'rank_test_score': array([ 87, 88, 24, 33, 34, 14, 40, 63, 79, 74, 46, 47, 16,\n",
" 23, 55, 135, 228, 114, 226, 174, 108, 131, 109, 146, 150, 145,\n",
" 128, 122, 117, 144, 247, 199, 240, 242, 203, 164, 205, 193, 197,\n",
" 200, 178, 231, 169, 189, 163, 243, 86, 3, 68, 70, 43, 84,\n",
" 19, 83, 80, 76, 81, 72, 59, 67, 270, 102, 232, 208, 209,\n",
" 239, 149, 138, 219, 101, 167, 166, 187, 142, 151, 246, 268, 244,\n",
" 259, 266, 262, 257, 265, 253, 267, 261, 255, 256, 260, 263, 2,\n",
" 82, 1, 11, 8, 48, 54, 15, 56, 27, 36, 20, 50, 49,\n",
" 12, 185, 97, 126, 160, 92, 93, 177, 132, 157, 129, 95, 134,\n",
" 165, 137, 127, 258, 198, 225, 221, 251, 107, 196, 229, 214, 250,\n",
" 182, 158, 194, 176, 235, 57, 85, 64, 51, 52, 10, 45, 22,\n",
" 73, 39, 7, 44, 4, 17, 25, 264, 245, 175, 96, 173, 119,\n",
" 98, 100, 104, 153, 105, 136, 125, 172, 112, 254, 238, 249, 162,\n",
" 183, 236, 224, 204, 170, 143, 116, 218, 223, 113, 156, 13, 5,\n",
" 62, 35, 77, 26, 65, 37, 53, 41, 75, 66, 21, 32, 38,\n",
" 171, 181, 133, 89, 154, 90, 220, 141, 118, 191, 152, 110, 121,\n",
" 106, 124, 269, 212, 180, 192, 211, 233, 206, 179, 190, 202, 227,\n",
" 234, 210, 130, 216, 91, 18, 30, 9, 42, 60, 78, 71, 29,\n",
" 61, 58, 69, 6, 28, 31, 237, 159, 248, 120, 111, 99, 147,\n",
" 168, 115, 148, 155, 186, 140, 103, 94, 222, 252, 184, 241, 123,\n",
" 139, 230, 215, 201, 207, 217, 161, 195, 213, 188], dtype=int32)}"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"clf.cv_results_"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Testen und Plotten\n",
"\n",
"Wenn mir anderem Datensatz getestet werden soll:\n",
"- Neuen Datensatz herunterladen und einlesen\n",
"- Eventuell `TEST_RANGE` anpassen\n",
"- Untere Zelle ausführen"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
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"text/plain": [
"<Figure size 1080x720 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"xaxis = range(0, TEST_RANGE[1])\n",
"plot.figure(figsize=(15,10))\n",
"plot.axvline(x=TRAINING_RANGE[0])\n",
"plot.axvline(x=TRAINING_RANGE[1])\n",
"plot.plot(xaxis, target, 'b', xaxis, clf.predict(data), 'r')\n",
"plot.legend(['Training','Test','TARGET OBD Speed','PREDICTED OBD Speed'])\n",
"plot.xlabel('Sample #')\n",
"plot.ylabel('OBD-Geschwindigkeit / 100km/h')\n",
"plot.title(\"ExtreTreesRegressor\")\n",
"plot.savefig('plot-ExtraTreesRegressor.pdf')\n",
"plot.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Anscheinend wird immer die höchste Geschwindigkeit vorrausgesagt, die der Regressor je gesehen hat. Wird er beispielsweise mit einer Landstraßenfahrt trainiert, ist auch auf der Autobahn bei 100 km/h Schluss."
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
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"text/plain": [
"<Figure size 1080x1497.6 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plot.figure(figsize = (15, 0.05*len(DATA_COLUMNS)))\n",
"importances = clf.best_estimator_.feature_importances_\n",
"stddev = np.var([t.feature_importances_ for t in clf.best_estimator_.estimators_], axis = 0)\n",
"sorted_indices = np.argsort(importances)[-30:]\n",
"plot.barh(np.array(DATA_COLUMNS)[sorted_indices], importances[sorted_indices], xerr = stddev[sorted_indices])\n",
"plot.ylabel('Feature')\n",
"plot.xlabel('Gewichtung (± Standardabweichung))')\n",
"plot.title(\"Feature-Gewichtung eines ExtreTreesRegressor\")\n",
"plot.savefig('plot-ExtraTreesRegressor-features.pdf')\n",
"plot.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Einige der Top-Features sprachen für starkes Overfitting:\n",
"- Temperatur und Luftfeuchtigkeit (`weat_temperature`, `weat_humidity`) bewegen kleinem Rahmen, und sollten auf das Fahrverhalten nur bedingten Einfluss haben (wenn überhaupt, nur auf längere Sicht gesehen; z.B. langsameres Fahren bei schlechtem Wetter).\n",
"- `join_idx` macht keinen Sinn.\n",
"- Position (Breiten- und Längengrad: `flt_latitude`, `latitude`, `longitude`, `flt_longitude`) funktionieren nur auf einer spezifischen Strecke. Das Lernen von Eigenheiten dieser Strecke ist nicht Aufgabe des Regressors; das sollte höchstens in anderen Datenquellen gespeichert und dann zur Berechnung hergezogen werden.\n",
"- Zeit und Entfernung (`hr_remainDistance`, `tt_calc_distance`, `ei_distance_lldist`, `hr_distance_lldist`, `gh_distance_lldist`, `time` etc.) sind schlecht auf andere Fahrten übertragbar; würde ich dieselbe Strecke von einem anderen Ausgangspunkt aus fahren, wäre die gesamte Vorhersage verschoben\n",
"- Windrichtung (`weat_windBearing`) hätte durchaus einen Einfluss (Rücken-/Gegenwind), allerdings nur, wenn die aktuelle Fahrtrichtung auch verwendet wird\n",
"\n",
"Diese Features wurden daher ausgeschlossen, was zu einer merklichen Verbesserung der Prädiktion führt (ist nun besser als HERE Maps in nahezu allen verwendeten Kriterien).\n",
"\n",
"Interessanterweise scheinen die Bäume allerdings vor allem eine Aggregation verschiedener Quellen für die Durchschnittsgeschwindigkeit zu sein …"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Gütekriterium - Prädiktion\n",
"\n",
"Berechung des Gütekritierums\n",
"- Root-mean-square deviation RMSE\n",
"- NRMSE Normalized root-mean-square deviation\n",
"- Mean absolute error MAE\n",
"- Mean absolute percentage error MAP\n",
"- Symmetric mean absolute percentage error\n",
"- https://en.wikipedia.org/wiki/Least_absolute_deviations\n",
"- https://en.wikipedia.org/wiki/Mean_signed_deviation\n",
"- Pearson Correlation Coefficient\n",
"- Accuracy (Interval of given size; absolute and relative)\n",
"- Median Absolute Deviation\n",
"\n",
"BITTE weitere Kriterien ergänzen\n"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"RMSE = 16.88 km/h\n",
"NRMSE = 26.48 %\n",
"MAE = 13.95 km/h\n",
"MAP = 21.98 %\n",
"SMAPE = 17.34 %\n",
"MSD = -9.15 km/h\n",
"CORR = 0.94\n",
"ACC_A = 40.67 %\n",
"ACC_R = 42.00 %\n",
"MAD = 13.49 km/h\n"
]
}
],
"source": [
"ta = target[TEST_RANGE[0]:TEST_RANGE[1]]\n",
"pr = clf.predict(data[TEST_RANGE[0]:TEST_RANGE[1]])\n",
"RMSE = math.sqrt(sum((ta-pr)**2)/len(ta))\n",
"print(\"RMSE = %.2f km/h\" %RMSE)\n",
"NRMSE = 1-math.sqrt(sum((ta-pr)**2))/math.sqrt(sum( (ta-np.mean(ta) )**2 ))\n",
"print(\"NRMSE = %.2f %%\" %(NRMSE*100))\n",
"MAE = sum(((ta-pr)**2)**(1/2))/len(ta)\n",
"print(\"MAE = %.2f km/h\" %MAE)\n",
"with np.errstate(divide = 'ignore'): map_elements = np.abs((ta - pr) / ta)\n",
"map_elements[map_elements == np.inf] = 0\n",
"MAP = np.sum(map_elements) / len(ta)\n",
"print(\"MAP = %.2f %%\" % (MAP*100))\n",
"SMAPE = np.sum(np.abs(ta - pr) / ((ta + pr) / 2)) / len(ta)\n",
"print(\"SMAPE = %.2f %%\" % (SMAPE*100))\n",
"MSD = np.sum(ta - pr) / len(ta)\n",
"print(\"MSD = %.2f km/h\" % MSD)\n",
"CORR = np.corrcoef(ta, pr)[1][0]\n",
"print(\"CORR = %.2f\" % CORR)\n",
"ACC_A_THRESHOLD = 10\n",
"ACC_A = (np.abs(ta - pr) < ACC_A_THRESHOLD).sum() / len(ta)\n",
"print(\"ACC_A = %.2f %%\" % (ACC_A*100))\n",
"ACC_R_THRESHOLD = 0.1\n",
"ACC_R = (np.abs(ta / pr - 1) < ACC_R_THRESHOLD).sum() / len(ta)\n",
"print(\"ACC_R = %.2f %%\" % (ACC_R*100))\n",
"MAD = np.median(np.abs(ta - pr))\n",
"print(\"MAD = %.2f km/h\" % MAD)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Vergleich mit HERE Maps Trafic Speed\n",
"Kann zum Vergleich sehr gut herangezogen werden ;)"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"RMSE = 16.82 km/h\n",
"NRMSE = 26.73 %\n",
"MAE = 14.06 km/h\n",
"MAP = 15.87 %\n",
"SMAPE = 16.62 %\n",
"MSD = 9.82 km/h\n",
"CORR = 0.81\n",
"ACC_A = 40.18 %\n",
"ACC_R = 32.00 %\n",
"MAD = 12.84 km/h\n"
]
}
],
"source": [
"ta = target[TEST_RANGE[0]:TEST_RANGE[1]]\n",
"pr = [row['hr_traficSpeed'] for row in reader_data] #t['hr_traficSpeed']\n",
"pr = np.array([float(d) if d != '' else 0.0 for d in pr])\n",
"pr = pr[TEST_RANGE[0]:TEST_RANGE[1]] * 3.6\n",
"RMSE = math.sqrt(sum((ta-pr)**2)/len(ta))\n",
"print(\"RMSE = %.2f km/h\" %RMSE)\n",
"NRMSE = 1-math.sqrt(sum((ta-pr)**2))/math.sqrt(sum( (ta-np.mean(ta) )**2 ))\n",
"print(\"NRMSE = %.2f %%\" %(NRMSE*100))\n",
"MAE = sum(((ta-pr)**2)**(1/2))/len(ta)\n",
"print(\"MAE = %.2f km/h\" %MAE)\n",
"with np.errstate(divide = 'ignore'): map_elements = np.abs((ta - pr) / ta)\n",
"map_elements[map_elements == np.inf] = 0\n",
"MAP = np.sum(map_elements) / len(ta)\n",
"print(\"MAP = %.2f %%\" % (MAP*100))\n",
"SMAPE = np.sum(np.abs(ta - pr) / ((ta + pr) / 2)) / len(ta)\n",
"print(\"SMAPE = %.2f %%\" % (SMAPE*100))\n",
"MSD = np.sum(ta - pr) / len(ta)\n",
"print(\"MSD = %.2f km/h\" % MSD)\n",
"CORR = np.corrcoef(ta, pr)[1][0]\n",
"print(\"CORR = %.2f\" % CORR)\n",
"ACC_A_THRESHOLD = 10\n",
"ACC_A = (np.abs(ta - pr) < ACC_A_THRESHOLD).sum() / len(ta)\n",
"print(\"ACC_A = %.2f %%\" % (ACC_A*100))\n",
"ACC_R_THRESHOLD = 0.1\n",
"ACC_R = (np.abs(ta / pr - 1) < ACC_R_THRESHOLD).sum() / len(ta)\n",
"print(\"ACC_R = %.2f %%\" % (ACC_R*100))\n",
"MAD = np.median(np.abs(ta - pr))\n",
"print(\"MAD = %.2f km/h\" % MAD)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Generalisierbarkeit\n",
"\n",
"Nach der abgeschlossenen Fahrt wird mit der ganzen Fahrt trainiert, und anschließend eine andere Fahrt vorhergesagt. Als Parameter werden die gefundenen Parameter der Grid Search beim ersten mal verwendet, wodurch sich der Vorgang erheblich beschleunigt."
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning:\n",
"\n",
"`max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
"\n"
]
},
{
"data": {
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],
"text/plain": [
"ExtraTreesRegressor(max_depth=10, max_features='auto', n_estimators=30)"
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"clf2 = ExtraTreesRegressor(n_estimators = clf.best_params_['n_estimators'],\n",
" max_depth = clf.best_params_['max_depth'],\n",
" max_features = clf.best_params_['max_features'])\n",
"clf2.fit(data, target)"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<BarContainer object of 416 artists>"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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"text/plain": [
"<Figure size 1080x7488 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plot.figure(figsize = (15, 0.25 * len(DATA_COLUMNS)))\n",
"importances = clf2.feature_importances_\n",
"stddev = np.var([t.feature_importances_ for t in clf2.estimators_], axis = 0)\n",
"sorted_indices = np.argsort(importances)\n",
"plot.barh(np.array(DATA_COLUMNS)[sorted_indices], importances[sorted_indices], xerr = stddev[sorted_indices])"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [],
"source": [
"SETUP_ID_2 = 450\n",
"\n",
"reader2 = runsql('select * from computeddata where setup_id = {} order by distance asc'.format(SETUP_ID_2))\n",
"reader_data2 = list(reader2) # list(...) so that following cells can be repeated"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [],
"source": [
"data2 = []\n",
"target2 = []\n",
"for row in reader_data2:\n",
" data2 += [[float(row[c]) if row[c] != '' else math.nan for c in DATA_COLUMNS]]\n",
" target2 += [float(row[TARGET_COLUMN]) if row[TARGET_COLUMN] != '' else math.nan]"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {},
"outputs": [],
"source": [
"data2 = imp.transform(data2)"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {},
"outputs": [],
"source": [
"np.savetxt('imputed-{}.csv'.format(SETUP_ID_2), data2, delimiter=',')\n",
"np.savetxt('target-{}.csv'.format(SETUP_ID_2), target2, delimiter=',')"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.legend.Legend at 0x7fcdd5567a30>"
]
},
"execution_count": 26,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 1080x720 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plot.figure(figsize=(15,10))\n",
"xaxis = range(0, len(target2))\n",
"plot.plot(xaxis, target2, 'b', xaxis, clf2.predict(data2), 'r')\n",
"plot.legend(['TARGET OBD Speed','PREDICTED OBD Speed'])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Wie bereits vorher festgestellt, scheint der Regressor mit höheren Geschwindigkeiten nicht vertraut. Trainieren wir also mit diesem Datensatz einen weiteren Regressor, und testen wieder mit einem anderen."
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning:\n",
"\n",
"`max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
"\n"
]
},
{
"data": {
"text/html": [
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],
"text/plain": [
"ExtraTreesRegressor(max_depth=10, max_features='auto', n_estimators=30)"
]
},
"execution_count": 27,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"clf3 = ExtraTreesRegressor(n_estimators = clf.best_params_['n_estimators'],\n",
" max_depth = clf.best_params_['max_depth'],\n",
" max_features = clf.best_params_['max_features'])\n",
"clf3.fit(data2, target2)"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {
"scrolled": false
},
"outputs": [
{
"data": {
"text/plain": [
"<BarContainer object of 416 artists>"
]
},
"execution_count": 28,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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"text/plain": [
"<Figure size 1080x7488 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plot.figure(figsize = (15, 0.25 * len(DATA_COLUMNS)))\n",
"importances = clf3.feature_importances_\n",
"stddev = np.var([t.feature_importances_ for t in clf3.estimators_], axis = 0)\n",
"sorted_indices = np.argsort(importances)\n",
"plot.barh(np.array(DATA_COLUMNS)[sorted_indices], importances[sorted_indices], xerr = stddev[sorted_indices])"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n"
]
}
],
"source": [
"SETUP_ID_3 = 888\n",
"\n",
"reader3 = runsql('select * from computeddata where setup_id = {} order by distance asc'.format(SETUP_ID_3))\n",
"reader_data3 = list(reader3) # list(...) so that following cells can be repeated"
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {},
"outputs": [],
"source": [
"data3 = []\n",
"target3 = []\n",
"for row in reader_data3:\n",
" data3 += [[float(row[c]) if row[c] != '' else math.nan for c in DATA_COLUMNS]]\n",
" target3 += [float(row[TARGET_COLUMN]) if row[TARGET_COLUMN] != '' else math.nan]"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {},
"outputs": [],
"source": [
"data3 = imp.transform(data3)"
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.legend.Legend at 0x7fcd8c9d5760>"
]
},
"execution_count": 32,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 1080x720 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plot.figure(figsize=(15,10))\n",
"xaxis = range(0, len(target3))\n",
"plot.plot(xaxis, target3, 'b', xaxis, clf3.predict(data3), 'r')\n",
"plot.legend(['TARGET OBD Speed','PREDICTED OBD Speed'])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Wir vergleichen die Prädiktion mit HERE Maps:"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"RMSE = 2.27 km/h\n",
"NRMSE = 92.08 %\n",
"MAE = 1.56 km/h\n",
"MAP = 1.72 %\n",
"SMAPE = 1.75 %\n",
"MSD = 0.94 km/h\n",
"CORR = 1.00\n",
"ACC_A = 99.78 %\n",
"ACC_R = 99.17 %\n",
"MAD = 1.15 km/h\n"
]
}
],
"source": [
"ta = target3\n",
"pr = clf3.predict(data3)\n",
"RMSE = math.sqrt(sum((ta-pr)**2)/len(ta))\n",
"print(\"RMSE = %.2f km/h\" %RMSE)\n",
"NRMSE = 1-math.sqrt(sum((ta-pr)**2))/math.sqrt(sum( (ta-np.mean(ta) )**2 ))\n",
"print(\"NRMSE = %.2f %%\" %(NRMSE*100))\n",
"MAE = sum(((ta-pr)**2)**(1/2))/len(ta)\n",
"print(\"MAE = %.2f km/h\" %MAE)\n",
"with np.errstate(divide = 'ignore'): map_elements = np.abs((ta - pr) / ta)\n",
"map_elements[map_elements == np.inf] = 0\n",
"MAP = np.sum(map_elements) / len(ta)\n",
"print(\"MAP = %.2f %%\" % (MAP*100))\n",
"SMAPE = np.sum(np.abs(ta - pr) / ((ta + pr) / 2)) / len(ta)\n",
"print(\"SMAPE = %.2f %%\" % (SMAPE*100))\n",
"MSD = np.sum(ta - pr) / len(ta)\n",
"print(\"MSD = %.2f km/h\" % MSD)\n",
"CORR = np.corrcoef(ta, pr)[1][0]\n",
"print(\"CORR = %.2f\" % CORR)\n",
"ACC_A_THRESHOLD = 10\n",
"ACC_A = (np.abs(ta - pr) < ACC_A_THRESHOLD).sum() / len(ta)\n",
"print(\"ACC_A = %.2f %%\" % (ACC_A*100))\n",
"ACC_R_THRESHOLD = 0.1\n",
"ACC_R = (np.abs(ta / pr - 1) < ACC_R_THRESHOLD).sum() / len(ta)\n",
"print(\"ACC_R = %.2f %%\" % (ACC_R*100))\n",
"MAD = np.median(np.abs(ta - pr))\n",
"print(\"MAD = %.2f km/h\" % MAD)"
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"RMSE = 21.57 km/h\n",
"NRMSE = 24.75 %\n",
"MAE = 16.79 km/h\n",
"MAP = 14.52 %\n",
"SMAPE = 15.78 %\n",
"MSD = 12.98 km/h\n",
"CORR = 0.81\n",
"ACC_A = 42.47 %\n",
"ACC_R = 35.90 %\n",
"MAD = 12.00 km/h\n"
]
}
],
"source": [
"ta = target3\n",
"pr = np.array([float(d['hr_traficSpeed']) if d['hr_traficSpeed'] != '' else 0.0 for d in reader_data3])\n",
"pr = pr * 3.6\n",
"RMSE = math.sqrt(sum((ta-pr)**2)/len(ta))\n",
"print(\"RMSE = %.2f km/h\" %RMSE)\n",
"NRMSE = 1-math.sqrt(sum((ta-pr)**2))/math.sqrt(sum( (ta-np.mean(ta) )**2 ))\n",
"print(\"NRMSE = %.2f %%\" %(NRMSE*100))\n",
"MAE = sum(((ta-pr)**2)**(1/2))/len(ta)\n",
"print(\"MAE = %.2f km/h\" %MAE)\n",
"with np.errstate(divide = 'ignore'): map_elements = np.abs((ta - pr) / ta)\n",
"map_elements[map_elements == np.inf] = 0\n",
"MAP = np.sum(map_elements) / len(ta)\n",
"print(\"MAP = %.2f %%\" % (MAP*100))\n",
"SMAPE = np.sum(np.abs(ta - pr) / ((ta + pr) / 2)) / len(ta)\n",
"print(\"SMAPE = %.2f %%\" % (SMAPE*100))\n",
"MSD = np.sum(ta - pr) / len(ta)\n",
"print(\"MSD = %.2f km/h\" % MSD)\n",
"CORR = np.corrcoef(ta, pr)[1][0]\n",
"print(\"CORR = %.2f\" % CORR)\n",
"ACC_A_THRESHOLD = 10\n",
"ACC_A = (np.abs(ta - pr) < ACC_A_THRESHOLD).sum() / len(ta)\n",
"print(\"ACC_A = %.2f %%\" % (ACC_A*100))\n",
"ACC_R_THRESHOLD = 0.1\n",
"ACC_R = (np.abs(ta / pr - 1) < ACC_R_THRESHOLD).sum() / len(ta)\n",
"print(\"ACC_R = %.2f %%\" % (ACC_R*100))\n",
"MAD = np.median(np.abs(ta - pr))\n",
"print(\"MAD = %.2f km/h\" % MAD)"
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {},
"outputs": [],
"source": [
"from sklearn.preprocessing import StandardScaler\n",
"scaler = StandardScaler()\n",
"scaler.fit(data[TRAINING_RANGE[0]:TRAINING_RANGE[1]])\n",
"\n",
"scaled_training_data = scaler.transform(data[TRAINING_RANGE[0]:TRAINING_RANGE[1]])\n",
"scaled_data = scaler.transform(data)\n",
"scaled_target = np.multiply(target, 0.01)"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {},
"outputs": [],
"source": [
"def gridsearch_train_and_plot(base, params = {}):\n",
" best_clf = gridsearch(base, params)\n",
" best_clf.fit(scaled_training_data, scaled_target[TRAINING_RANGE[0]:TRAINING_RANGE[1]])\n",
" xaxis = range(0, TEST_RANGE[1])\n",
" print(best_clf.best_params_)\n",
" plot.figure(figsize=(15,10))\n",
" plot.axvline(x=TRAINING_RANGE[0])\n",
" plot.axvline(x=TRAINING_RANGE[1])\n",
" plot.plot(xaxis, scaled_target, 'b', xaxis, np.maximum(-1.0, np.minimum(4.0, best_clf.predict(scaled_data))), 'rx')\n",
" plot.legend(['Training','Test','TARGET OBD Speed','PREDICTED OBD Speed'])\n",
" plot.xlabel('Sample #')\n",
" plot.ylabel('OBD-Geschwindigkeit / 100km/h')\n",
" name = type(base).__name__\n",
" plot.title(name)\n",
" plot.savefig(f'plot-{name}.pdf')\n",
" plot.show()"
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'gamma': 'scale', 'kernel': 'linear'}\n"
]
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 1080x720 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"from sklearn import svm\n",
"gridsearch_train_and_plot(svm.SVR(),\n",
" {'kernel': ['linear', 'poly', 'rbf', 'sigmoid'],\n",
" 'gamma': ['scale', 'auto']})"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"gridsearch_train_and_plot(svm.NuSVR(),\n",
" {'kernel': ['linear', 'poly', 'rbf', 'sigmoid'],\n",
" 'gamma': ['scale', 'auto']})"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from sklearn import linear_model\n",
"gridsearch_train_and_plot(linear_model.SGDRegressor(),\n",
" {'loss': ['squared_loss', 'huber', 'epsilon_insensitive', 'squared_epsilon_insensitive'],\n",
" 'penalty': ['l1', 'l2', 'elasticnet']})"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from sklearn import neighbors\n",
"gridsearch_train_and_plot(neighbors.KNeighborsRegressor(),\n",
" {'n_neighbors': [5, 10, 20, 50, 100, 200, 500],\n",
" 'weights': ['uniform', 'distance']})"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# i think something is borked in there\n",
"gridsearch_train_and_plot(neighbors.RadiusNeighborsRegressor(),\n",
" {'radius': [0.0001, 0.0002, 0.0005, 0.001, 0.002, 0.005, 0.01, 0.02, 0.05, 0.1, 0.2, 0.5, 1.0],\n",
" 'weights': ['uniform', 'distance']})"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from sklearn import gaussian_process\n",
"gridsearch_train_and_plot(gaussian_process.GaussianProcessRegressor(),\n",
" {'normalize_y': [True, False]})"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.10"
}
},
"nbformat": 4,
"nbformat_minor": 2
}