{
"cells": [
{
"cell_type": "markdown",
"id": "complicated-pontiac",
"metadata": {},
"source": [
"## 04_modeling_m_dtree\n",
" \n",
"Mourad Askar\n",
"\n",
"**Decision Tree Models to predict if a crash has_injuries**\n",
"\n",
"**NOTE: This model was experimental for exploration of the tree, but not included in the analysis**\n",
" \n",
"Create Models to predict if a crash has_injuries: \n",
"- 0: NO INJURY\n",
"- 1: HAS INJURY \n",
"\n",
"Steps per Model:\n",
"- Create 2019 Model using Training and Validation split\n",
" - Use Grid Search to find best hyperparameters\n",
" - Grid Search will use 2019 Training set for CrossValidation\n",
"- Using 2019 Fitted Model\n",
" - Test 2019 Model on 2019 test data with best hyperparameters\n",
" - Test 2019 Model on 2020 data with best hyperparameters\n",
"- Handling Class Imbalance\n",
" - Each model is tested using class_weight='balanced'\n",
" - Then Each model is tested using a resampled dataset\n",
"\n",
"Report for each model run: \n",
"- Best Hyperparameters\n",
"- Model scores"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "extraordinary-sheriff",
"metadata": {
"execution": {
"iopub.execute_input": "2021-03-21T20:50:07.372201Z",
"iopub.status.busy": "2021-03-21T20:50:07.372027Z",
"iopub.status.idle": "2021-03-21T20:50:09.368087Z",
"shell.execute_reply": "2021-03-21T20:50:09.367242Z",
"shell.execute_reply.started": "2021-03-21T20:50:07.372157Z"
},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"python 3.9.2\n",
"numpy 1.20.1\n",
"pandas 1.2.3\n",
"klib 0.1.5\n",
"sklearn 0.24.1\n",
"sweetviz 2.0.9\n"
]
}
],
"source": [
"import pandas as pd\n",
"import numpy as np\n",
"import klib\n",
"import pandas_profiling as pp\n",
"import sweetviz\n",
"import sklearn\n",
"\n",
"import matplotlib.pyplot as plt\n",
"import seaborn as sns\n",
"\n",
"from sklearn.preprocessing import OrdinalEncoder\n",
"from sklearn.preprocessing import OneHotEncoder\n",
"from sklearn.preprocessing import StandardScaler\n",
"from sklearn.preprocessing import MinMaxScaler\n",
"from sklearn.compose import make_column_transformer\n",
"\n",
"from imblearn.over_sampling import *\n",
"from imblearn.under_sampling import *\n",
"\n",
"from sklearn.utils import *\n",
"from sklearn.model_selection import train_test_split\n",
"from platform import python_version\n",
"\n",
"from sklearn.tree import export_graphviz\n",
"import graphviz\n",
"\n",
"%precision 2\n",
"\n",
"pd.options.display.max_rows = 100\n",
"pd.options.display.max_columns = 100\n",
"pd.options.display.width = 120\n",
"pd.options.display.float_format='{:,.2f}'.format\n",
"pd.options.display.precision = 2\n",
"\n",
"np.set_printoptions(precision=2, linewidth=120, suppress=True, edgeitems=5)\n",
"\n",
"sns.set_style(\"white\")\n",
"\n",
"StartBold = \"\\033[1m\"\n",
"EndBold = \"\\033[0m\"\n",
"\n",
"print('python',python_version())\n",
"print(np.__name__, np.__version__)\n",
"print(pd.__name__, pd.__version__)\n",
"print(klib.__name__, klib.__version__)\n",
"#print(pp.__name__, pp.__version__)\n",
"print(sklearn.__name__, sklearn.__version__)\n",
"print(sweetviz.__name__, sweetviz.__version__)"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "architectural-rouge",
"metadata": {
"execution": {
"iopub.execute_input": "2021-03-21T20:50:09.370488Z",
"iopub.status.busy": "2021-03-21T20:50:09.370194Z",
"iopub.status.idle": "2021-03-21T20:50:09.373681Z",
"shell.execute_reply": "2021-03-21T20:50:09.373149Z",
"shell.execute_reply.started": "2021-03-21T20:50:09.370471Z"
},
"tags": []
},
"outputs": [],
"source": [
"from sklearn.model_selection import GridSearchCV\n",
"from sklearn.model_selection import cross_validate\n",
"\n",
"from sklearn.tree import DecisionTreeClassifier, plot_tree\n",
"from sklearn.ensemble import RandomForestClassifier, BaggingClassifier\n",
"from sklearn.linear_model import LogisticRegression, SGDClassifier\n",
"from sklearn.ensemble import AdaBoostClassifier\n",
"from sklearn.ensemble import GradientBoostingClassifier\n",
"\n",
"from sklearn.svm import SVC\n",
"\n",
"from sklearn import metrics"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "generous-tourist",
"metadata": {
"execution": {
"iopub.execute_input": "2021-03-21T20:50:09.374581Z",
"iopub.status.busy": "2021-03-21T20:50:09.374464Z",
"iopub.status.idle": "2021-03-21T20:50:09.384361Z",
"shell.execute_reply": "2021-03-21T20:50:09.383243Z",
"shell.execute_reply.started": "2021-03-21T20:50:09.374565Z"
},
"tags": []
},
"outputs": [],
"source": [
"%matplotlib inline\n",
"%config InlineBackend.figure_formats = ['retina']\n",
"#%config InlineBackend.figure_formats = ['png', 'retina', 'jpeg', 'svg', 'pdf']"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "framed-segment",
"metadata": {
"execution": {
"iopub.execute_input": "2021-03-21T20:50:09.386783Z",
"iopub.status.busy": "2021-03-21T20:50:09.386368Z",
"iopub.status.idle": "2021-03-21T20:50:09.389745Z",
"shell.execute_reply": "2021-03-21T20:50:09.389141Z",
"shell.execute_reply.started": "2021-03-21T20:50:09.386761Z"
},
"tags": []
},
"outputs": [],
"source": [
"# Global Parameters\n",
"\n",
"random_state = 2021\n",
"n_jobs = 4"
]
},
{
"cell_type": "markdown",
"id": "needed-danger",
"metadata": {},
"source": [
"# Define Dictionary Mappers"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "swiss-convenience",
"metadata": {
"execution": {
"iopub.execute_input": "2021-03-21T20:50:09.390618Z",
"iopub.status.busy": "2021-03-21T20:50:09.390483Z",
"iopub.status.idle": "2021-03-21T20:50:09.393211Z",
"shell.execute_reply": "2021-03-21T20:50:09.392682Z",
"shell.execute_reply.started": "2021-03-21T20:50:09.390600Z"
},
"tags": []
},
"outputs": [],
"source": [
"week_days = {0:'Sunday',1:'Monday',2:'Tuesday',3:'Wednesday',4:'Thursday',5:'Friday',6:'Saturday'}\n",
"is_weekday = {0:'Weekend',1:'Weekday'}"
]
},
{
"cell_type": "markdown",
"id": "qualified-impression",
"metadata": {},
"source": [
"# Read Data"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "enclosed-volume",
"metadata": {
"execution": {
"iopub.execute_input": "2021-03-21T20:50:09.394173Z",
"iopub.status.busy": "2021-03-21T20:50:09.394031Z",
"iopub.status.idle": "2021-03-21T20:50:09.703715Z",
"shell.execute_reply": "2021-03-21T20:50:09.702589Z",
"shell.execute_reply.started": "2021-03-21T20:50:09.394154Z"
},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"Int64Index: 326488 entries, 0 to 328789\n",
"Data columns (total 32 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 crash_date 326488 non-null datetime64[ns]\n",
" 1 crash_year 326488 non-null int16 \n",
" 2 crash_month 326488 non-null int8 \n",
" 3 crash_day_of_week 326488 non-null int8 \n",
" 4 crash_hour 326488 non-null int8 \n",
" 5 crash_time_of_day 326488 non-null category \n",
" 6 latitude 326488 non-null float32 \n",
" 7 longitude 326488 non-null float32 \n",
" 8 beat_of_occurrence 326488 non-null int64 \n",
" 9 address 326488 non-null string \n",
" 10 street_no 326488 non-null string \n",
" 11 street_direction 326488 non-null category \n",
" 12 street_name 326488 non-null category \n",
" 13 posted_speed_limit 326488 non-null int64 \n",
" 14 traffic_control_device 326488 non-null category \n",
" 15 device_condition 326488 non-null category \n",
" 16 weather_condition 326488 non-null category \n",
" 17 lighting_condition 326488 non-null category \n",
" 18 trafficway_type 326488 non-null category \n",
" 19 alignment 326488 non-null category \n",
" 20 roadway_surface_cond 326488 non-null category \n",
" 21 road_defect 326488 non-null category \n",
" 22 first_crash_type 326488 non-null category \n",
" 23 prim_contributory_cause 326488 non-null category \n",
" 24 sec_contributory_cause 326488 non-null category \n",
" 25 num_units 326488 non-null int8 \n",
" 26 has_injuries 326488 non-null int64 \n",
" 27 has_fatal 326488 non-null int64 \n",
" 28 crash_type 326488 non-null category \n",
" 29 damage 326488 non-null category \n",
" 30 injuries_total 326488 non-null int64 \n",
" 31 injuries_fatal 326488 non-null int64 \n",
"dtypes: category(16), datetime64[ns](1), float32(2), int16(1), int64(6), int8(4), string(2)\n",
"memory usage: 34.6 MB\n"
]
}
],
"source": [
"#file_parquet_c = '20210203_chi_crashes_c.parquet'\n",
"#file_parquet_c = '20210228_chi_crashes_c.parquet'\n",
"file_crash_df_parquet = 'crash_df.parquet'\n",
"\n",
"crash_df = pd.read_parquet(file_crash_df_parquet)\n",
"\n",
"crash_df.info()"
]
},
{
"cell_type": "markdown",
"id": "saved-sunglasses",
"metadata": {},
"source": [
"# Engineer New Features"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "cardiovascular-yugoslavia",
"metadata": {
"execution": {
"iopub.execute_input": "2021-03-21T20:50:09.706689Z",
"iopub.status.busy": "2021-03-21T20:50:09.706488Z",
"iopub.status.idle": "2021-03-21T20:50:09.795893Z",
"shell.execute_reply": "2021-03-21T20:50:09.795384Z",
"shell.execute_reply.started": "2021-03-21T20:50:09.706672Z"
},
"tags": []
},
"outputs": [],
"source": [
"crash_df['is_weekday'] = crash_df.crash_day_of_week.map(lambda x: 0 if x in [1,7] else 1)\n"
]
},
{
"cell_type": "markdown",
"id": "substantial-principle",
"metadata": {},
"source": [
"# Select Features of interest"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "pacific-spectacular",
"metadata": {
"execution": {
"iopub.execute_input": "2021-03-21T20:50:09.798448Z",
"iopub.status.busy": "2021-03-21T20:50:09.798279Z",
"iopub.status.idle": "2021-03-21T20:50:09.804630Z",
"shell.execute_reply": "2021-03-21T20:50:09.803941Z",
"shell.execute_reply.started": "2021-03-21T20:50:09.798409Z"
},
"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
"['crash_year',\n",
" 'crash_month',\n",
" 'crash_time_of_day',\n",
" 'is_weekday',\n",
" 'latitude',\n",
" 'longitude',\n",
" 'posted_speed_limit',\n",
" 'traffic_control_device',\n",
" 'device_condition',\n",
" 'weather_condition',\n",
" 'lighting_condition',\n",
" 'trafficway_type',\n",
" 'alignment',\n",
" 'roadway_surface_cond',\n",
" 'road_defect',\n",
" 'first_crash_type',\n",
" 'prim_contributory_cause',\n",
" 'sec_contributory_cause',\n",
" 'num_units',\n",
" 'has_injuries']"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"features_names = [\n",
"# 'crash_date',\n",
" 'crash_year',\n",
" 'crash_month',\n",
"# 'crash_day_of_week',\n",
"# 'crash_hour',\n",
" 'crash_time_of_day', # New\n",
" 'is_weekday', #New\n",
" 'latitude',\n",
" 'longitude',\n",
"# 'beat_of_occurrence', # Should be considered as categorical, don't scale.\n",
"# 'address',\n",
"# 'street_no',\n",
"# 'street_direction',\n",
"# 'street_name',\n",
" 'posted_speed_limit',\n",
" 'traffic_control_device',\n",
" 'device_condition',\n",
" 'weather_condition',\n",
" 'lighting_condition',\n",
" 'trafficway_type',\n",
" 'alignment',\n",
" 'roadway_surface_cond',\n",
" 'road_defect',\n",
" 'first_crash_type',\n",
" 'prim_contributory_cause',\n",
" 'sec_contributory_cause',\n",
" 'num_units',\n",
"# 'intersection_related_i',\n",
"# 'not_right_of_way_i',\n",
"# 'hit_and_run_i',\n",
"]\n",
"\n",
"target_names = [\n",
" 'has_injuries', # New\n",
"# 'has_fatal', # New\n",
"# 'crash_type',\n",
"# 'damage',\n",
"# 'injuries_total',\n",
"# 'injuries_fatal',\n",
"# 'injuries_incapacitating',\n",
"# 'inj_non_incap',\n",
"# 'inj_report_not_evdnt',\n",
"# 'injuries_no_indication',\n",
"# 'most_severe_injury',\n",
"]\n",
"\n",
"all_columns = features_names + target_names\n",
"all_columns"
]
},
{
"cell_type": "markdown",
"id": "brown-pound",
"metadata": {},
"source": [
"# Filter for only 2019"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "southwest-moral",
"metadata": {
"execution": {
"iopub.execute_input": "2021-03-21T20:50:09.806003Z",
"iopub.status.busy": "2021-03-21T20:50:09.805823Z",
"iopub.status.idle": "2021-03-21T20:50:09.872626Z",
"shell.execute_reply": "2021-03-21T20:50:09.872088Z",
"shell.execute_reply.started": "2021-03-21T20:50:09.805971Z"
},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"Int64Index: 116737 entries, 118947 to 236699\n",
"Data columns (total 19 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 crash_month 116737 non-null int8 \n",
" 1 crash_time_of_day 116737 non-null category\n",
" 2 is_weekday 116737 non-null int64 \n",
" 3 latitude 116737 non-null float32 \n",
" 4 longitude 116737 non-null float32 \n",
" 5 posted_speed_limit 116737 non-null int64 \n",
" 6 traffic_control_device 116737 non-null category\n",
" 7 device_condition 116737 non-null category\n",
" 8 weather_condition 116737 non-null category\n",
" 9 lighting_condition 116737 non-null category\n",
" 10 trafficway_type 116737 non-null category\n",
" 11 alignment 116737 non-null category\n",
" 12 roadway_surface_cond 116737 non-null category\n",
" 13 road_defect 116737 non-null category\n",
" 14 first_crash_type 116737 non-null category\n",
" 15 prim_contributory_cause 116737 non-null category\n",
" 16 sec_contributory_cause 116737 non-null category\n",
" 17 num_units 116737 non-null int8 \n",
" 18 has_injuries 116737 non-null int64 \n",
"dtypes: category(12), float32(2), int64(3), int8(2)\n",
"memory usage: 6.0 MB\n"
]
}
],
"source": [
"#crash_df = crash_df[(crash_df.crash_year>2017) & (crash_df.crash_year<2021)]\n",
"crash_2019_df = crash_df.query('crash_year == 2019')[all_columns[1:]] # drop year column\n",
"crash_2019_df.info()"
]
},
{
"cell_type": "markdown",
"id": "split-milwaukee",
"metadata": {},
"source": [
"# Determine features / target"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "enclosed-average",
"metadata": {
"execution": {
"iopub.execute_input": "2021-03-21T20:50:09.873588Z",
"iopub.status.busy": "2021-03-21T20:50:09.873452Z",
"iopub.status.idle": "2021-03-21T20:50:09.881270Z",
"shell.execute_reply": "2021-03-21T20:50:09.880734Z",
"shell.execute_reply.started": "2021-03-21T20:50:09.873570Z"
},
"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
"((116737, 18), (116737,))"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"features = crash_2019_df[features_names[1:]].copy() # skip year column\n",
"target = crash_2019_df[target_names].has_injuries.copy()\n",
"\n",
"features.shape, target.shape"
]
},
{
"cell_type": "markdown",
"id": "lasting-trinity",
"metadata": {},
"source": [
"# Encode Categorical"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "married-clearing",
"metadata": {
"execution": {
"iopub.execute_input": "2021-03-21T20:50:09.882351Z",
"iopub.status.busy": "2021-03-21T20:50:09.882180Z",
"iopub.status.idle": "2021-03-21T20:50:09.907467Z",
"shell.execute_reply": "2021-03-21T20:50:09.906846Z",
"shell.execute_reply.started": "2021-03-21T20:50:09.882332Z"
},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"Int64Index: 116737 entries, 118947 to 236699\n",
"Data columns (total 18 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 crash_month 116737 non-null int8 \n",
" 1 crash_time_of_day 116737 non-null category\n",
" 2 is_weekday 116737 non-null int64 \n",
" 3 latitude 116737 non-null float32 \n",
" 4 longitude 116737 non-null float32 \n",
" 5 posted_speed_limit 116737 non-null int64 \n",
" 6 traffic_control_device 116737 non-null category\n",
" 7 device_condition 116737 non-null category\n",
" 8 weather_condition 116737 non-null category\n",
" 9 lighting_condition 116737 non-null category\n",
" 10 trafficway_type 116737 non-null category\n",
" 11 alignment 116737 non-null category\n",
" 12 roadway_surface_cond 116737 non-null category\n",
" 13 road_defect 116737 non-null category\n",
" 14 first_crash_type 116737 non-null category\n",
" 15 prim_contributory_cause 116737 non-null category\n",
" 16 sec_contributory_cause 116737 non-null category\n",
" 17 num_units 116737 non-null int8 \n",
"dtypes: category(12), float32(2), int64(2), int8(2)\n",
"memory usage: 5.1 MB\n"
]
}
],
"source": [
"features.info()"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "heated-tragedy",
"metadata": {
"execution": {
"iopub.execute_input": "2021-03-21T20:50:09.908710Z",
"iopub.status.busy": "2021-03-21T20:50:09.908414Z",
"iopub.status.idle": "2021-03-21T20:50:09.919256Z",
"shell.execute_reply": "2021-03-21T20:50:09.918603Z",
"shell.execute_reply.started": "2021-03-21T20:50:09.908686Z"
},
"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
"array(['crash_time_of_day', 'traffic_control_device', 'device_condition', 'weather_condition', 'lighting_condition',\n",
" 'trafficway_type', 'alignment', 'roadway_surface_cond', 'road_defect', 'first_crash_type',\n",
" 'prim_contributory_cause', 'sec_contributory_cause'], dtype=object)"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"features.select_dtypes('category').columns.values"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "present-digit",
"metadata": {
"execution": {
"iopub.execute_input": "2021-03-21T20:50:09.920541Z",
"iopub.status.busy": "2021-03-21T20:50:09.920298Z",
"iopub.status.idle": "2021-03-21T20:50:09.925528Z",
"shell.execute_reply": "2021-03-21T20:50:09.925008Z",
"shell.execute_reply.started": "2021-03-21T20:50:09.920515Z"
},
"tags": []
},
"outputs": [],
"source": [
"features['crash_month'] = features['crash_month'].astype('category')\n",
"#features['beat_of_occurrence'] = features['beat_of_occurrence'].astype('category')\n",
"#features['address'] = features['address'].astype('category')"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "approved-fence",
"metadata": {
"execution": {
"iopub.execute_input": "2021-03-21T20:50:09.926379Z",
"iopub.status.busy": "2021-03-21T20:50:09.926244Z",
"iopub.status.idle": "2021-03-21T20:50:09.996426Z",
"shell.execute_reply": "2021-03-21T20:50:09.995799Z",
"shell.execute_reply.started": "2021-03-21T20:50:09.926360Z"
},
"tags": []
},
"outputs": [],
"source": [
"features_dm = pd.get_dummies(features)"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "stylish-trustee",
"metadata": {
"execution": {
"iopub.execute_input": "2021-03-21T20:50:09.997852Z",
"iopub.status.busy": "2021-03-21T20:50:09.997654Z",
"iopub.status.idle": "2021-03-21T20:50:10.004087Z",
"shell.execute_reply": "2021-03-21T20:50:10.003401Z",
"shell.execute_reply.started": "2021-03-21T20:50:09.997829Z"
},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"X and y shapes:\n",
"(116737, 204) (116737,) \n",
"\n",
"Target Ratio:\n",
"0 0.86\n",
"1 0.14\n",
"Name: has_injuries, dtype: float64 \n",
"\n"
]
}
],
"source": [
"# Split data in to Features X and Target y\n",
"X = features_dm\n",
"y = target\n",
"print('X and y shapes:')\n",
"print(X.shape,y.shape,'\\n')\n",
"print('Target Ratio:')\n",
"print(y.value_counts(normalize=True, dropna=False),'\\n')"
]
},
{
"cell_type": "code",
"execution_count": 16,
"id": "focal-hunter",
"metadata": {
"execution": {
"iopub.execute_input": "2021-03-21T20:50:10.005231Z",
"iopub.status.busy": "2021-03-21T20:50:10.004997Z",
"iopub.status.idle": "2021-03-21T20:50:10.124951Z",
"shell.execute_reply": "2021-03-21T20:50:10.124470Z",
"shell.execute_reply.started": "2021-03-21T20:50:10.005204Z"
},
"tags": []
},
"outputs": [
{
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"</table>\n",
"<p>116737 rows × 204 columns</p>\n",
"</div>"
],
"text/plain": [
" is_weekday latitude longitude posted_speed_limit num_units crash_month_1 crash_month_2 crash_month_3 \\\n",
"118947 1 41.88 -87.71 30 2 1 0 0 \n",
"118948 1 41.79 -87.59 35 2 1 0 0 \n",
"118949 1 41.95 -87.67 30 2 1 0 0 \n",
"118950 1 41.88 -87.63 20 2 1 0 0 \n",
"118951 1 41.95 -87.78 30 3 1 0 0 \n",
"... ... ... ... ... ... ... ... ... \n",
"236694 1 41.84 -87.64 30 2 0 0 0 \n",
"236695 1 41.88 -87.67 25 2 0 0 0 \n",
"236696 1 41.91 -87.63 45 4 0 0 0 \n",
"236698 1 41.81 -87.74 30 1 0 0 0 \n",
"236699 1 41.87 -87.70 35 3 0 0 0 \n",
"\n",
" crash_month_4 crash_month_5 crash_month_6 crash_month_7 crash_month_8 crash_month_9 crash_month_10 \\\n",
"118947 0 0 0 0 0 0 0 \n",
"118948 0 0 0 0 0 0 0 \n",
"118949 0 0 0 0 0 0 0 \n",
"118950 0 0 0 0 0 0 0 \n",
"118951 0 0 0 0 0 0 0 \n",
"... ... ... ... ... ... ... ... \n",
"236694 0 0 0 0 0 0 0 \n",
"236695 0 0 0 0 0 0 0 \n",
"236696 0 0 0 0 0 0 0 \n",
"236698 0 0 0 0 0 0 0 \n",
"236699 0 0 0 0 0 0 0 \n",
"\n",
" crash_month_11 crash_month_12 crash_time_of_day_overnight crash_time_of_day_morning \\\n",
"118947 0 0 1 0 \n",
"118948 0 0 1 0 \n",
"118949 0 0 1 0 \n",
"118950 0 0 1 0 \n",
"118951 0 0 1 0 \n",
"... ... ... ... ... \n",
"236694 0 1 0 0 \n",
"236695 0 1 0 0 \n",
"236696 0 1 0 0 \n",
"236698 0 1 0 0 \n",
"236699 0 1 0 0 \n",
"\n",
" crash_time_of_day_mid_day crash_time_of_day_evening traffic_control_device_BICYCLE CROSSING SIGN \\\n",
"118947 0 0 0 \n",
"118948 0 0 0 \n",
"118949 0 0 0 \n",
"118950 0 0 0 \n",
"118951 0 0 0 \n",
"... ... ... ... \n",
"236694 0 1 0 \n",
"236695 0 1 0 \n",
"236696 0 1 0 \n",
"236698 0 1 0 \n",
"236699 0 1 0 \n",
"\n",
" traffic_control_device_DELINEATORS traffic_control_device_FLASHING CONTROL SIGNAL \\\n",
"118947 0 0 \n",
"118948 0 0 \n",
"118949 0 0 \n",
"118950 0 0 \n",
"118951 0 0 \n",
"... ... ... \n",
"236694 0 0 \n",
"236695 0 0 \n",
"236696 0 0 \n",
"236698 0 0 \n",
"236699 0 0 \n",
"\n",
" traffic_control_device_LANE USE MARKING traffic_control_device_NO CONTROLS \\\n",
"118947 0 1 \n",
"118948 0 1 \n",
"118949 0 1 \n",
"118950 0 0 \n",
"118951 0 1 \n",
"... ... ... \n",
"236694 0 0 \n",
"236695 0 0 \n",
"236696 0 1 \n",
"236698 0 1 \n",
"236699 0 1 \n",
"\n",
" traffic_control_device_NO PASSING traffic_control_device_OTHER \\\n",
"118947 0 0 \n",
"118948 0 0 \n",
"118949 0 0 \n",
"118950 0 0 \n",
"118951 0 0 \n",
"... ... ... \n",
"236694 0 0 \n",
"236695 0 0 \n",
"236696 0 0 \n",
"236698 0 0 \n",
"236699 0 0 \n",
"\n",
" traffic_control_device_OTHER RAILROAD CROSSING traffic_control_device_OTHER REG. SIGN \\\n",
"118947 0 0 \n",
"118948 0 0 \n",
"118949 0 0 \n",
"118950 0 0 \n",
"118951 0 0 \n",
"... ... ... \n",
"236694 0 0 \n",
"236695 0 0 \n",
"236696 0 0 \n",
"236698 0 0 \n",
"236699 0 0 \n",
"\n",
" traffic_control_device_OTHER WARNING SIGN traffic_control_device_PEDESTRIAN CROSSING SIGN \\\n",
"118947 0 0 \n",
"118948 0 0 \n",
"118949 0 0 \n",
"118950 0 0 \n",
"118951 0 0 \n",
"... ... ... \n",
"236694 0 0 \n",
"236695 0 0 \n",
"236696 0 0 \n",
"236698 0 0 \n",
"236699 0 0 \n",
"\n",
" traffic_control_device_POLICE/FLAGMAN traffic_control_device_RAILROAD CROSSING GATE \\\n",
"118947 0 0 \n",
"118948 0 0 \n",
"118949 0 0 \n",
"118950 0 0 \n",
"118951 0 0 \n",
"... ... ... \n",
"236694 0 0 \n",
"236695 0 0 \n",
"236696 0 0 \n",
"236698 0 0 \n",
"236699 0 0 \n",
"\n",
" traffic_control_device_RR CROSSING SIGN traffic_control_device_SCHOOL ZONE \\\n",
"118947 0 0 \n",
"118948 0 0 \n",
"118949 0 0 \n",
"118950 0 0 \n",
"118951 0 0 \n",
"... ... ... \n",
"236694 0 0 \n",
"236695 0 0 \n",
"236696 0 0 \n",
"236698 0 0 \n",
"236699 0 0 \n",
"\n",
" traffic_control_device_STOP SIGN/FLASHER traffic_control_device_TRAFFIC SIGNAL \\\n",
"118947 0 0 \n",
"118948 0 0 \n",
"118949 0 0 \n",
"118950 0 1 \n",
"118951 0 0 \n",
"... ... ... \n",
"236694 1 0 \n",
"236695 1 0 \n",
"236696 0 0 \n",
"236698 0 0 \n",
"236699 0 0 \n",
"\n",
" traffic_control_device_UNKNOWN traffic_control_device_YIELD device_condition_FUNCTIONING IMPROPERLY \\\n",
"118947 0 0 0 \n",
"118948 0 0 0 \n",
"118949 0 0 0 \n",
"118950 0 0 0 \n",
"118951 0 0 0 \n",
"... ... ... ... \n",
"236694 0 0 0 \n",
"236695 0 0 0 \n",
"236696 0 0 0 \n",
"236698 0 0 0 \n",
"236699 0 0 0 \n",
"\n",
" device_condition_FUNCTIONING PROPERLY device_condition_MISSING device_condition_NO CONTROLS \\\n",
"118947 0 0 1 \n",
"118948 0 0 1 \n",
"118949 0 0 1 \n",
"118950 1 0 0 \n",
"118951 0 0 1 \n",
"... ... ... ... \n",
"236694 1 0 0 \n",
"236695 0 0 0 \n",
"236696 0 0 1 \n",
"236698 0 0 1 \n",
"236699 0 0 1 \n",
"\n",
" device_condition_NOT FUNCTIONING device_condition_OTHER device_condition_UNKNOWN \\\n",
"118947 0 0 0 \n",
"118948 0 0 0 \n",
"118949 0 0 0 \n",
"118950 0 0 0 \n",
"118951 0 0 0 \n",
"... ... ... ... \n",
"236694 0 0 0 \n",
"236695 0 0 1 \n",
"236696 0 0 0 \n",
"236698 0 0 0 \n",
"236699 0 0 0 \n",
"\n",
" device_condition_WORN REFLECTIVE MATERIAL weather_condition_BLOWING SAND, SOIL, DIRT \\\n",
"118947 0 0 \n",
"118948 0 0 \n",
"118949 0 0 \n",
"118950 0 0 \n",
"118951 0 0 \n",
"... ... ... \n",
"236694 0 0 \n",
"236695 0 0 \n",
"236696 0 0 \n",
"236698 0 0 \n",
"236699 0 0 \n",
"\n",
" weather_condition_BLOWING SNOW ... prim_contributory_cause_PHYSICAL CONDITION OF DRIVER \\\n",
"118947 0 ... 0 \n",
"118948 0 ... 0 \n",
"118949 0 ... 0 \n",
"118950 0 ... 0 \n",
"118951 0 ... 0 \n",
"... ... ... ... \n",
"236694 0 ... 0 \n",
"236695 0 ... 0 \n",
"236696 0 ... 0 \n",
"236698 0 ... 0 \n",
"236699 0 ... 0 \n",
"\n",
" prim_contributory_cause_RELATED TO BUS STOP prim_contributory_cause_ROAD CONSTRUCTION/MAINTENANCE \\\n",
"118947 0 0 \n",
"118948 0 0 \n",
"118949 0 0 \n",
"118950 0 0 \n",
"118951 0 0 \n",
"... ... ... \n",
"236694 0 0 \n",
"236695 0 0 \n",
"236696 0 0 \n",
"236698 0 0 \n",
"236699 0 0 \n",
"\n",
" prim_contributory_cause_ROAD ENGINEERING/SURFACE/MARKING DEFECTS prim_contributory_cause_TEXTING \\\n",
"118947 0 0 \n",
"118948 0 0 \n",
"118949 0 0 \n",
"118950 0 0 \n",
"118951 0 0 \n",
"... ... ... \n",
"236694 0 0 \n",
"236695 0 0 \n",
"236696 0 0 \n",
"236698 0 0 \n",
"236699 0 0 \n",
"\n",
" prim_contributory_cause_TURNING RIGHT ON RED prim_contributory_cause_UNABLE TO DETERMINE \\\n",
"118947 0 1 \n",
"118948 0 1 \n",
"118949 0 1 \n",
"118950 0 0 \n",
"118951 0 0 \n",
"... ... ... \n",
"236694 0 1 \n",
"236695 0 1 \n",
"236696 0 0 \n",
"236698 0 1 \n",
"236699 0 0 \n",
"\n",
" prim_contributory_cause_UNDER THE INFLUENCE OF ALCOHOL/DRUGS (USE WHEN ARREST IS EFFECTED) \\\n",
"118947 0 \n",
"118948 0 \n",
"118949 0 \n",
"118950 0 \n",
"118951 0 \n",
"... ... \n",
"236694 0 \n",
"236695 0 \n",
"236696 0 \n",
"236698 0 \n",
"236699 0 \n",
"\n",
" prim_contributory_cause_VISION OBSCURED (SIGNS, TREE LIMBS, BUILDINGS, ETC.) prim_contributory_cause_WEATHER \\\n",
"118947 0 0 \n",
"118948 0 0 \n",
"118949 0 0 \n",
"118950 0 0 \n",
"118951 0 0 \n",
"... ... ... \n",
"236694 0 0 \n",
"236695 0 0 \n",
"236696 0 0 \n",
"236698 0 0 \n",
"236699 0 0 \n",
"\n",
" sec_contributory_cause_ANIMAL sec_contributory_cause_BICYCLE ADVANCING LEGALLY ON RED LIGHT \\\n",
"118947 0 0 \n",
"118948 0 0 \n",
"118949 0 0 \n",
"118950 0 0 \n",
"118951 0 0 \n",
"... ... ... \n",
"236694 0 0 \n",
"236695 0 0 \n",
"236696 0 0 \n",
"236698 0 0 \n",
"236699 0 0 \n",
"\n",
" sec_contributory_cause_CELL PHONE USE OTHER THAN TEXTING \\\n",
"118947 0 \n",
"118948 0 \n",
"118949 0 \n",
"118950 0 \n",
"118951 0 \n",
"... ... \n",
"236694 0 \n",
"236695 0 \n",
"236696 0 \n",
"236698 0 \n",
"236699 0 \n",
"\n",
" sec_contributory_cause_DISREGARDING OTHER TRAFFIC SIGNS sec_contributory_cause_DISREGARDING ROAD MARKINGS \\\n",
"118947 0 0 \n",
"118948 0 0 \n",
"118949 0 0 \n",
"118950 0 1 \n",
"118951 0 0 \n",
"... ... ... \n",
"236694 0 0 \n",
"236695 0 0 \n",
"236696 0 0 \n",
"236698 0 0 \n",
"236699 0 0 \n",
"\n",
" sec_contributory_cause_DISREGARDING STOP SIGN sec_contributory_cause_DISREGARDING TRAFFIC SIGNALS \\\n",
"118947 0 0 \n",
"118948 0 0 \n",
"118949 0 0 \n",
"118950 0 0 \n",
"118951 0 0 \n",
"... ... ... \n",
"236694 0 0 \n",
"236695 0 0 \n",
"236696 0 0 \n",
"236698 0 0 \n",
"236699 0 0 \n",
"\n",
" sec_contributory_cause_DISREGARDING YIELD SIGN sec_contributory_cause_DISTRACTION - FROM INSIDE VEHICLE \\\n",
"118947 0 0 \n",
"118948 0 0 \n",
"118949 0 0 \n",
"118950 0 0 \n",
"118951 0 0 \n",
"... ... ... \n",
"236694 0 0 \n",
"236695 0 0 \n",
"236696 0 0 \n",
"236698 0 0 \n",
"236699 0 0 \n",
"\n",
" sec_contributory_cause_DISTRACTION - FROM OUTSIDE VEHICLE \\\n",
"118947 0 \n",
"118948 0 \n",
"118949 0 \n",
"118950 0 \n",
"118951 0 \n",
"... ... \n",
"236694 0 \n",
"236695 0 \n",
"236696 0 \n",
"236698 0 \n",
"236699 0 \n",
"\n",
" sec_contributory_cause_DISTRACTION - OTHER ELECTRONIC DEVICE (NAVIGATION DEVICE, DVD PLAYER, ETC.) \\\n",
"118947 0 \n",
"118948 0 \n",
"118949 0 \n",
"118950 0 \n",
"118951 0 \n",
"... ... \n",
"236694 0 \n",
"236695 0 \n",
"236696 0 \n",
"236698 0 \n",
"236699 0 \n",
"\n",
" sec_contributory_cause_DRIVING ON WRONG SIDE/WRONG WAY \\\n",
"118947 0 \n",
"118948 0 \n",
"118949 0 \n",
"118950 0 \n",
"118951 0 \n",
"... ... \n",
"236694 0 \n",
"236695 0 \n",
"236696 0 \n",
"236698 0 \n",
"236699 0 \n",
"\n",
" sec_contributory_cause_DRIVING SKILLS/KNOWLEDGE/EXPERIENCE \\\n",
"118947 0 \n",
"118948 0 \n",
"118949 0 \n",
"118950 0 \n",
"118951 0 \n",
"... ... \n",
"236694 0 \n",
"236695 0 \n",
"236696 0 \n",
"236698 0 \n",
"236699 0 \n",
"\n",
" sec_contributory_cause_EQUIPMENT - VEHICLE CONDITION \\\n",
"118947 0 \n",
"118948 0 \n",
"118949 0 \n",
"118950 0 \n",
"118951 0 \n",
"... ... \n",
"236694 0 \n",
"236695 0 \n",
"236696 0 \n",
"236698 0 \n",
"236699 0 \n",
"\n",
" sec_contributory_cause_EVASIVE ACTION DUE TO ANIMAL, OBJECT, NONMOTORIST \\\n",
"118947 0 \n",
"118948 0 \n",
"118949 0 \n",
"118950 0 \n",
"118951 0 \n",
"... ... \n",
"236694 0 \n",
"236695 0 \n",
"236696 0 \n",
"236698 0 \n",
"236699 0 \n",
"\n",
" sec_contributory_cause_EXCEEDING AUTHORIZED SPEED LIMIT \\\n",
"118947 0 \n",
"118948 0 \n",
"118949 0 \n",
"118950 0 \n",
"118951 0 \n",
"... ... \n",
"236694 0 \n",
"236695 0 \n",
"236696 0 \n",
"236698 0 \n",
"236699 0 \n",
"\n",
" sec_contributory_cause_EXCEEDING SAFE SPEED FOR CONDITIONS \\\n",
"118947 0 \n",
"118948 0 \n",
"118949 0 \n",
"118950 0 \n",
"118951 0 \n",
"... ... \n",
"236694 0 \n",
"236695 0 \n",
"236696 0 \n",
"236698 0 \n",
"236699 0 \n",
"\n",
" sec_contributory_cause_FAILING TO REDUCE SPEED TO AVOID CRASH \\\n",
"118947 0 \n",
"118948 0 \n",
"118949 0 \n",
"118950 0 \n",
"118951 1 \n",
"... ... \n",
"236694 0 \n",
"236695 0 \n",
"236696 1 \n",
"236698 0 \n",
"236699 0 \n",
"\n",
" sec_contributory_cause_FAILING TO YIELD RIGHT-OF-WAY sec_contributory_cause_FOLLOWING TOO CLOSELY \\\n",
"118947 0 0 \n",
"118948 0 0 \n",
"118949 0 0 \n",
"118950 0 0 \n",
"118951 0 0 \n",
"... ... ... \n",
"236694 0 0 \n",
"236695 0 0 \n",
"236696 0 0 \n",
"236698 0 0 \n",
"236699 0 0 \n",
"\n",
" sec_contributory_cause_HAD BEEN DRINKING (USE WHEN ARREST IS NOT MADE) \\\n",
"118947 0 \n",
"118948 0 \n",
"118949 0 \n",
"118950 0 \n",
"118951 0 \n",
"... ... \n",
"236694 0 \n",
"236695 0 \n",
"236696 0 \n",
"236698 0 \n",
"236699 0 \n",
"\n",
" sec_contributory_cause_IMPROPER BACKING sec_contributory_cause_IMPROPER LANE USAGE \\\n",
"118947 0 0 \n",
"118948 0 0 \n",
"118949 0 0 \n",
"118950 0 0 \n",
"118951 0 0 \n",
"... ... ... \n",
"236694 0 0 \n",
"236695 0 0 \n",
"236696 0 0 \n",
"236698 0 0 \n",
"236699 0 0 \n",
"\n",
" sec_contributory_cause_IMPROPER OVERTAKING/PASSING sec_contributory_cause_IMPROPER TURNING/NO SIGNAL \\\n",
"118947 0 0 \n",
"118948 0 0 \n",
"118949 0 0 \n",
"118950 0 0 \n",
"118951 0 0 \n",
"... ... ... \n",
"236694 0 0 \n",
"236695 0 0 \n",
"236696 0 0 \n",
"236698 0 0 \n",
"236699 0 0 \n",
"\n",
" sec_contributory_cause_MOTORCYCLE ADVANCING LEGALLY ON RED LIGHT sec_contributory_cause_NOT APPLICABLE \\\n",
"118947 0 0 \n",
"118948 0 0 \n",
"118949 0 0 \n",
"118950 0 0 \n",
"118951 0 0 \n",
"... ... ... \n",
"236694 0 1 \n",
"236695 0 0 \n",
"236696 0 0 \n",
"236698 0 0 \n",
"236699 0 0 \n",
"\n",
" sec_contributory_cause_OBSTRUCTED CROSSWALKS \\\n",
"118947 0 \n",
"118948 0 \n",
"118949 0 \n",
"118950 0 \n",
"118951 0 \n",
"... ... \n",
"236694 0 \n",
"236695 0 \n",
"236696 0 \n",
"236698 0 \n",
"236699 0 \n",
"\n",
" sec_contributory_cause_OPERATING VEHICLE IN ERRATIC, RECKLESS, CARELESS, NEGLIGENT OR AGGRESSIVE MANNER \\\n",
"118947 0 \n",
"118948 0 \n",
"118949 0 \n",
"118950 0 \n",
"118951 0 \n",
"... ... \n",
"236694 0 \n",
"236695 0 \n",
"236696 0 \n",
"236698 0 \n",
"236699 0 \n",
"\n",
" sec_contributory_cause_PASSING STOPPED SCHOOL BUS sec_contributory_cause_PHYSICAL CONDITION OF DRIVER \\\n",
"118947 0 0 \n",
"118948 0 0 \n",
"118949 0 0 \n",
"118950 0 0 \n",
"118951 0 0 \n",
"... ... ... \n",
"236694 0 0 \n",
"236695 0 0 \n",
"236696 0 0 \n",
"236698 0 0 \n",
"236699 0 0 \n",
"\n",
" sec_contributory_cause_RELATED TO BUS STOP sec_contributory_cause_ROAD CONSTRUCTION/MAINTENANCE \\\n",
"118947 0 0 \n",
"118948 0 0 \n",
"118949 0 0 \n",
"118950 0 0 \n",
"118951 0 0 \n",
"... ... ... \n",
"236694 0 0 \n",
"236695 0 0 \n",
"236696 0 0 \n",
"236698 0 0 \n",
"236699 0 0 \n",
"\n",
" sec_contributory_cause_ROAD ENGINEERING/SURFACE/MARKING DEFECTS sec_contributory_cause_TEXTING \\\n",
"118947 0 0 \n",
"118948 0 0 \n",
"118949 0 0 \n",
"118950 0 0 \n",
"118951 0 0 \n",
"... ... ... \n",
"236694 0 0 \n",
"236695 0 0 \n",
"236696 0 0 \n",
"236698 0 0 \n",
"236699 0 0 \n",
"\n",
" sec_contributory_cause_TURNING RIGHT ON RED sec_contributory_cause_UNABLE TO DETERMINE \\\n",
"118947 0 1 \n",
"118948 0 1 \n",
"118949 0 1 \n",
"118950 0 0 \n",
"118951 0 0 \n",
"... ... ... \n",
"236694 0 0 \n",
"236695 0 1 \n",
"236696 0 0 \n",
"236698 0 1 \n",
"236699 0 1 \n",
"\n",
" sec_contributory_cause_UNDER THE INFLUENCE OF ALCOHOL/DRUGS (USE WHEN ARREST IS EFFECTED) \\\n",
"118947 0 \n",
"118948 0 \n",
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"[116737 rows x 204 columns]"
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"X"
]
},
{
"cell_type": "markdown",
"id": "balanced-jordan",
"metadata": {},
"source": [
"# Create Train/Test datasets"
]
},
{
"cell_type": "code",
"execution_count": 17,
"id": "elementary-stranger",
"metadata": {
"execution": {
"iopub.execute_input": "2021-03-21T20:50:10.125976Z",
"iopub.status.busy": "2021-03-21T20:50:10.125826Z",
"iopub.status.idle": "2021-03-21T20:50:10.292077Z",
"shell.execute_reply": "2021-03-21T20:50:10.291579Z",
"shell.execute_reply.started": "2021-03-21T20:50:10.125956Z"
},
"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
"((93389, 204), (23348, 204), (93389,), (23348,))"
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Split data into Train and Test\n",
"# We stratify to make sure target representation is kept in the new datasets\n",
"X_train, X_test, y_train, y_test = train_test_split(X, y,\n",
" test_size=.2,\n",
"# stratify=y,\n",
" random_state=random_state)\n",
"X_train.shape, X_test.shape, y_train.shape, y_test.shape"
]
},
{
"cell_type": "code",
"execution_count": 18,
"id": "placed-corps",
"metadata": {
"execution": {
"iopub.execute_input": "2021-03-21T20:50:10.293013Z",
"iopub.status.busy": "2021-03-21T20:50:10.292871Z",
"iopub.status.idle": "2021-03-21T20:50:10.299258Z",
"shell.execute_reply": "2021-03-21T20:50:10.298703Z",
"shell.execute_reply.started": "2021-03-21T20:50:10.292994Z"
},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Training Data:\n",
"--------------\n",
"X and y shapes:\n",
"(93389, 204) (93389,) \n",
"\n",
"Target Ratio:\n",
"0 0.86\n",
"1 0.14\n",
"Name: has_injuries, dtype: float64 \n",
"\n"
]
}
],
"source": [
"print('Training Data:')\n",
"print('--------------')\n",
"print('X and y shapes:')\n",
"print(X_train.shape,y_train.shape,'\\n')\n",
"print('Target Ratio:')\n",
"print(y_train.value_counts(normalize=True, dropna=False),'\\n')"
]
},
{
"cell_type": "code",
"execution_count": 19,
"id": "extended-magnitude",
"metadata": {
"execution": {
"iopub.execute_input": "2021-03-21T20:50:10.300261Z",
"iopub.status.busy": "2021-03-21T20:50:10.300118Z",
"iopub.status.idle": "2021-03-21T20:50:10.305204Z",
"shell.execute_reply": "2021-03-21T20:50:10.304573Z",
"shell.execute_reply.started": "2021-03-21T20:50:10.300241Z"
},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Testing Data:\n",
"-------------\n",
"X and y shapes:\n",
"(23348, 204) (23348,) \n",
"\n",
"Target Ratio:\n",
"0 0.86\n",
"1 0.14\n",
"Name: has_injuries, dtype: float64 \n",
"\n"
]
}
],
"source": [
"print('Testing Data:')\n",
"print('-------------')\n",
"print('X and y shapes:')\n",
"print(X_test.shape,y_test.shape,'\\n')\n",
"print('Target Ratio:')\n",
"print(y_test.value_counts(normalize=True, dropna=False),'\\n')"
]
},
{
"cell_type": "markdown",
"id": "cathedral-attempt",
"metadata": {},
"source": [
"It's visible that we have an imbalanced target that we need to consider during our evaluations."
]
},
{
"cell_type": "markdown",
"id": "robust-logan",
"metadata": {},
"source": [
"# Resampling"
]
},
{
"cell_type": "markdown",
"id": "diagnostic-bicycle",
"metadata": {},
"source": [
"Resampling to compensate the target class that has low representation."
]
},
{
"cell_type": "code",
"execution_count": 20,
"id": "rational-cover",
"metadata": {
"execution": {
"iopub.execute_input": "2021-03-21T20:50:10.306490Z",
"iopub.status.busy": "2021-03-21T20:50:10.306269Z",
"iopub.status.idle": "2021-03-21T20:50:11.366272Z",
"shell.execute_reply": "2021-03-21T20:50:11.365583Z",
"shell.execute_reply.started": "2021-03-21T20:50:10.306467Z"
},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Testing Data:\n",
"-------------\n",
"X and y shapes:\n",
"(160788, 204) (160788,) \n",
"\n",
"Target Ratio:\n",
"0 0.50\n",
"1 0.50\n",
"Name: has_injuries, dtype: float64 \n",
"\n"
]
}
],
"source": [
"ros = RandomOverSampler(random_state=random_state)\n",
"X_train_resampled, y_train_resampled = ros.fit_resample(X_train, y_train)\n",
"\n",
"print('Testing Data:')\n",
"print('-------------')\n",
"print('X and y shapes:')\n",
"print(X_train_resampled.shape,y_train_resampled.shape,'\\n')\n",
"print('Target Ratio:')\n",
"print(y_train_resampled.value_counts(normalize=True, dropna=False),'\\n')"
]
},
{
"cell_type": "code",
"execution_count": 21,
"id": "finite-yellow",
"metadata": {
"execution": {
"iopub.execute_input": "2021-03-21T20:50:11.367384Z",
"iopub.status.busy": "2021-03-21T20:50:11.367092Z",
"iopub.status.idle": "2021-03-21T20:50:11.436287Z",
"shell.execute_reply": "2021-03-21T20:50:11.435723Z",
"shell.execute_reply.started": "2021-03-21T20:50:11.367361Z"
},
"tags": []
},
"outputs": [
{
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" <th>latitude</th>\n",
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" <th>crash_time_of_day_evening</th>\n",
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" <th>sec_contributory_cause_PASSING STOPPED SCHOOL BUS</th>\n",
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" <th>sec_contributory_cause_ROAD ENGINEERING/SURFACE/MARKING DEFECTS</th>\n",
" <th>sec_contributory_cause_TEXTING</th>\n",
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" <tr>\n",
" <th>210973</th>\n",
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" </tbody>\n",
"</table>\n",
"<p>93389 rows × 204 columns</p>\n",
"</div>"
],
"text/plain": [
" is_weekday latitude longitude posted_speed_limit num_units crash_month_1 crash_month_2 crash_month_3 \\\n",
"209921 1 41.85 -87.69 25 2 0 0 0 \n",
"120062 0 41.98 -87.67 25 2 1 0 0 \n",
"205935 1 41.90 -87.62 35 2 0 0 0 \n",
"154446 1 41.92 -87.76 35 2 0 0 0 \n",
"156371 1 41.74 -87.68 35 5 0 0 0 \n",
"... ... ... ... ... ... ... ... ... \n",
"121631 1 41.79 -87.80 30 2 1 0 0 \n",
"202702 0 41.94 -87.69 30 2 0 0 0 \n",
"125175 1 41.68 -87.73 20 2 1 0 0 \n",
"213271 1 41.89 -87.62 30 2 0 0 0 \n",
"210973 1 41.95 -87.72 30 2 0 0 0 \n",
"\n",
" crash_month_4 crash_month_5 crash_month_6 crash_month_7 crash_month_8 crash_month_9 crash_month_10 \\\n",
"209921 0 0 0 0 0 0 1 \n",
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" crash_month_11 crash_month_12 crash_time_of_day_overnight crash_time_of_day_morning \\\n",
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"\n",
" crash_time_of_day_mid_day crash_time_of_day_evening traffic_control_device_BICYCLE CROSSING SIGN \\\n",
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" traffic_control_device_DELINEATORS traffic_control_device_FLASHING CONTROL SIGNAL \\\n",
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" traffic_control_device_LANE USE MARKING traffic_control_device_NO CONTROLS \\\n",
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" traffic_control_device_OTHER RAILROAD CROSSING traffic_control_device_OTHER REG. SIGN \\\n",
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" traffic_control_device_OTHER WARNING SIGN traffic_control_device_PEDESTRIAN CROSSING SIGN \\\n",
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" traffic_control_device_POLICE/FLAGMAN traffic_control_device_RAILROAD CROSSING GATE \\\n",
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" traffic_control_device_RR CROSSING SIGN traffic_control_device_SCHOOL ZONE \\\n",
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" traffic_control_device_STOP SIGN/FLASHER traffic_control_device_TRAFFIC SIGNAL \\\n",
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" traffic_control_device_UNKNOWN traffic_control_device_YIELD device_condition_FUNCTIONING IMPROPERLY \\\n",
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" device_condition_FUNCTIONING PROPERLY device_condition_MISSING device_condition_NO CONTROLS \\\n",
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" device_condition_NOT FUNCTIONING device_condition_OTHER device_condition_UNKNOWN \\\n",
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" device_condition_WORN REFLECTIVE MATERIAL weather_condition_BLOWING SAND, SOIL, DIRT \\\n",
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" weather_condition_BLOWING SNOW ... prim_contributory_cause_PHYSICAL CONDITION OF DRIVER \\\n",
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" prim_contributory_cause_RELATED TO BUS STOP prim_contributory_cause_ROAD CONSTRUCTION/MAINTENANCE \\\n",
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" prim_contributory_cause_ROAD ENGINEERING/SURFACE/MARKING DEFECTS prim_contributory_cause_TEXTING \\\n",
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" prim_contributory_cause_TURNING RIGHT ON RED prim_contributory_cause_UNABLE TO DETERMINE \\\n",
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" prim_contributory_cause_UNDER THE INFLUENCE OF ALCOHOL/DRUGS (USE WHEN ARREST IS EFFECTED) \\\n",
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" prim_contributory_cause_VISION OBSCURED (SIGNS, TREE LIMBS, BUILDINGS, ETC.) prim_contributory_cause_WEATHER \\\n",
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" sec_contributory_cause_ANIMAL sec_contributory_cause_BICYCLE ADVANCING LEGALLY ON RED LIGHT \\\n",
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" sec_contributory_cause_CELL PHONE USE OTHER THAN TEXTING \\\n",
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" sec_contributory_cause_DISREGARDING OTHER TRAFFIC SIGNS sec_contributory_cause_DISREGARDING ROAD MARKINGS \\\n",
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" sec_contributory_cause_DISREGARDING STOP SIGN sec_contributory_cause_DISREGARDING TRAFFIC SIGNALS \\\n",
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"... ... ... \n",
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" sec_contributory_cause_DISREGARDING YIELD SIGN sec_contributory_cause_DISTRACTION - FROM INSIDE VEHICLE \\\n",
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"... ... ... \n",
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" sec_contributory_cause_DISTRACTION - FROM OUTSIDE VEHICLE \\\n",
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"... ... \n",
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" sec_contributory_cause_DISTRACTION - OTHER ELECTRONIC DEVICE (NAVIGATION DEVICE, DVD PLAYER, ETC.) \\\n",
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"... ... \n",
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" sec_contributory_cause_DRIVING ON WRONG SIDE/WRONG WAY \\\n",
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"... ... \n",
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" sec_contributory_cause_DRIVING SKILLS/KNOWLEDGE/EXPERIENCE \\\n",
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" sec_contributory_cause_EQUIPMENT - VEHICLE CONDITION \\\n",
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" sec_contributory_cause_EVASIVE ACTION DUE TO ANIMAL, OBJECT, NONMOTORIST \\\n",
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" sec_contributory_cause_EXCEEDING AUTHORIZED SPEED LIMIT \\\n",
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" sec_contributory_cause_EXCEEDING SAFE SPEED FOR CONDITIONS \\\n",
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"209921 0 0 \n",
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"\n",
" sec_contributory_cause_MOTORCYCLE ADVANCING LEGALLY ON RED LIGHT sec_contributory_cause_NOT APPLICABLE \\\n",
"209921 0 1 \n",
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" sec_contributory_cause_PASSING STOPPED SCHOOL BUS sec_contributory_cause_PHYSICAL CONDITION OF DRIVER \\\n",
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"\n",
"[93389 rows x 204 columns]"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"X_train"
]
},
{
"cell_type": "markdown",
"id": "liable-practice",
"metadata": {},
"source": [
"# Scaling Data"
]
},
{
"cell_type": "markdown",
"id": "technological-organization",
"metadata": {},
"source": [
"I have considered whether I should scale/normalize the dataset, then I realized that most of my features are categorical that are now expanded into 1 hot encoded dummy variables. The other Integer variables I also assume that they can be used as is, as they can represent ordinal values. Anyway, I will be testing the normalization during my steps.\n",
"\n",
"**NOTE: Decided that scaling will make sense to be applied on posted_speed_limit and num_units**"
]
},
{
"cell_type": "code",
"execution_count": 22,
"id": "above-creativity",
"metadata": {
"execution": {
"iopub.execute_input": "2021-03-21T20:50:11.437182Z",
"iopub.status.busy": "2021-03-21T20:50:11.437047Z",
"iopub.status.idle": "2021-03-21T20:50:12.088522Z",
"shell.execute_reply": "2021-03-21T20:50:12.088027Z",
"shell.execute_reply.started": "2021-03-21T20:50:11.437164Z"
},
"tags": []
},
"outputs": [],
"source": [
"X_train_Scaler = MinMaxScaler().fit(X_train)\n",
"X_train_mms = X_train_Scaler.transform(X_train) # mms = MinMaxScaled\n",
"\n",
"X_train_resampled_Scaler = MinMaxScaler().fit(X_train_resampled)\n",
"X_train_resampled_mms = X_train_resampled_Scaler.transform(X_train_resampled)\n",
"\n",
"X_test_mms = X_train_Scaler.transform(X_test)\n",
"X_test_rs_mms = X_train_resampled_Scaler.transform(X_test)"
]
},
{
"cell_type": "code",
"execution_count": 23,
"id": "iraqi-thumb",
"metadata": {
"execution": {
"iopub.execute_input": "2021-03-21T20:50:12.089443Z",
"iopub.status.busy": "2021-03-21T20:50:12.089305Z",
"iopub.status.idle": "2021-03-21T20:50:12.093654Z",
"shell.execute_reply": "2021-03-21T20:50:12.093059Z",
"shell.execute_reply.started": "2021-03-21T20:50:12.089424Z"
},
"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
"array([[1. , 0.54, 0.59, 0.42, 0.09, ..., 0. , 0. , 0. , 0. , 0. ],\n",
" [0. , 0.89, 0.65, 0.42, 0.09, ..., 0. , 0. , 0. , 0. , 0. ],\n",
" [1. , 0.66, 0.77, 0.58, 0.09, ..., 0. , 0. , 0. , 0. , 0. ],\n",
" [1. , 0.73, 0.43, 0.58, 0.09, ..., 0. , 0. , 0. , 0. , 0. ],\n",
" [1. , 0.26, 0.61, 0.58, 0.36, ..., 0. , 0. , 0. , 0. , 0. ],\n",
" ...,\n",
" [1. , 0.4 , 0.33, 0.5 , 0.09, ..., 0. , 1. , 0. , 0. , 0. ],\n",
" [0. , 0.78, 0.6 , 0.5 , 0.09, ..., 0. , 0. , 0. , 0. , 0. ],\n",
" [1. , 0.1 , 0.51, 0.33, 0.09, ..., 0. , 1. , 0. , 0. , 0. ],\n",
" [1. , 0.65, 0.76, 0.5 , 0.09, ..., 0. , 1. , 0. , 0. , 0. ],\n",
" [1. , 0.82, 0.52, 0.5 , 0.09, ..., 0. , 1. , 0. , 0. , 0. ]])"
]
},
"execution_count": 23,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"X_train_mms"
]
},
{
"cell_type": "markdown",
"id": "wound-heating",
"metadata": {},
"source": [
"# Helper Functions"
]
},
{
"cell_type": "code",
"execution_count": 24,
"id": "happy-permit",
"metadata": {
"execution": {
"iopub.execute_input": "2021-03-21T20:50:12.094865Z",
"iopub.status.busy": "2021-03-21T20:50:12.094584Z",
"iopub.status.idle": "2021-03-21T20:50:12.111498Z",
"shell.execute_reply": "2021-03-21T20:50:12.110755Z",
"shell.execute_reply.started": "2021-03-21T20:50:12.094843Z"
},
"tags": []
},
"outputs": [],
"source": [
"def get_GS_cv_results(gs):\n",
" _cv_results_ = gs.cv_results_\n",
" _scorer_keys = gs.scorer_.keys()\n",
"\n",
" df_gs_scores = pd.DataFrame()\n",
"\n",
" for k in _cv_results_.keys():\n",
" if k.startswith('param_'):\n",
" param_key = ('param',k.split('_',1)[1])\n",
" param_values = _cv_results_[k]\n",
" df_gs_scores = pd.concat([df_gs_scores,pd.DataFrame({param_key:param_values})], axis=1)\n",
"\n",
" elif k.startswith('mean_train') or k.startswith('mean_test'):\n",
" score_key = (k.split('_',2)[2],k.split('_',2)[1])\n",
" score_results = _cv_results_[k]\n",
" df_gs_scores = pd.concat([df_gs_scores,pd.DataFrame({score_key:score_results})], axis=1)\n",
"\n",
" return df_gs_scores\n",
"\n",
"def plot_grid_search_scores_grid(gs, display_plots=False):\n",
" _cv_results_ = gs.cv_results_\n",
" _scorer_keys = gs.scorer_.keys()\n",
" _param_keys = list(_cv_results_['params'][0].keys())\n",
" df_gs_scores = get_GS_cv_results(gs)\n",
" \n",
" display(df_gs_scores)\n",
" \n",
" if(display_plots):\n",
" if len(_param_keys) > 1:\n",
" for _score in _scorer_keys:\n",
" dd = df_gs_scores[['param',_score]]\n",
" dd.columns = dd.columns.droplevel(0)\n",
" ddm = dd.melt(id_vars=_param_keys[:2],value_vars=['train','test'],var_name='dataset',value_name=_score)\n",
" g = sns.FacetGrid(ddm,col=_param_keys[0],height=3)\n",
" g.map_dataframe(sns.lineplot,_param_keys[1],_score,'dataset')\n",
" g.add_legend()\n",
" else:\n",
" for _score in _scorer_keys:\n",
" dd = df_gs_scores[['param',_score]]\n",
" dd.columns = dd.columns.droplevel(0)\n",
" ddm = dd.melt(id_vars=_param_keys,value_vars=['train','test'],var_name='dataset',value_name=_score)\n",
" g = sns.FacetGrid(ddm, height=3)\n",
" g.map_dataframe(sns.lineplot,_param_keys[0],_score,'dataset')\n",
" g.add_legend()\n",
"\n",
"def plot_grid_search_results(gs, plot_scoring='r2'):\n",
" _cv_results_ = gs.cv_results_\n",
" _scorer_keys = gs.scorer_.keys()\n",
" \n",
" print(f'{StartBold}Estimator:{EndBold}')\n",
" print(gs.best_estimator_)\n",
" print()\n",
" print(f'{StartBold}Best Result (Suggested):{EndBold}')\n",
" print(f'{StartBold}\\t{\"\":20} {\"train\":>6} {\"valdn\":>6}{EndBold}')\n",
" for _score in _scorer_keys:\n",
" print('\\t{2:>20} {0:>6.2f} {1:>6.2f}'.format(_cv_results_['mean_train_' + _score][gs.best_index_],\n",
" _cv_results_['mean_test_' + _score][gs.best_index_],\n",
" _score))\n",
" print()\n",
" print(f'{StartBold}Params:{EndBold}')\n",
" print('\\t{}'.format(gs.best_params_))\n",
" print()\n",
" \n",
" \n",
" scoring_label = plot_scoring\n",
" not_negative = 1\n",
" if plot_scoring.startswith('neg_'):\n",
" scoring_label = plot_scoring[4:]\n",
" not_negative = -1\n",
" df = pd.DataFrame({\n",
" 'params': _cv_results_['params'],\n",
" 'mean_train_' + plot_scoring: _cv_results_['mean_train_' + plot_scoring] * not_negative,\n",
" 'mean_test_' + plot_scoring: _cv_results_['mean_test_' + plot_scoring] * not_negative\n",
" })\n",
" fig, ax = plt.subplots()\n",
" df.plot('params',['mean_train_' + plot_scoring,'mean_test_' + plot_scoring], 'line', ax=ax)\n",
" ax.axvline(gs.best_index_,0,1, color='r', linestyle='--')\n",
" plt.grid(axis='both',c='lightgrey',ls=':')\n",
" plt.xticks(ticks=range(df.params.count()), labels=df.params)\n",
" plt.tick_params(axis='x', rotation=90)\n",
" plt.ylabel(scoring_label)\n",
" plt.legend(['train','valdn'])\n",
" plt.show()\n",
" \n",
" if(\"beep\" in globals()): beep(True)\n",
" \n",
"def score_classification_model(fitted_model, X, y_true):\n",
" p = fitted_model.predict(X)\n",
" print('accuracy score: {:>5.2f}'.format(metrics.accuracy_score(y_true,p)))\n",
" print('f1 score: {:>5.2f}'.format(metrics.f1_score(y_true,p)))\n",
" print('recall score: {:>5.2f}'.format(metrics.recall_score(y_true,p)))\n",
" print('precision score: {:>5.2f}'.format(metrics.precision_score(y_true,p)))\n",
" print('balanced_accuracy score: {:>5.2f}'.format(metrics.balanced_accuracy_score(y_true,p)))\n",
" print('roc_auc score: {:>5.2f}'.format(metrics.roc_auc_score(y_true,p)))\n",
" #print(metrics.classification_report(y_true,p))\n",
" metrics.plot_confusion_matrix(fitted_model,X, y_true)\n",
" plt.show()\n",
" #print(metrics.classification_report(y_true,p, sample_weight=compute_sample_weight('balanced',y_true)))\n",
" #metrics.plot_confusion_matrix(fitted_model,X, y_true, sample_weight=compute_sample_weight('balanced',y_true))\n",
" \n",
"def plot_coefficients(coef, feature_names, top_n=0):\n",
" _ = pd.DataFrame({'features':feature_names,'coef':coef}).sort_values('coef',key=lambda x: abs(x),ascending=False)\n",
" if top_n > 0:\n",
" _ = _.iloc[:top_n,:]\n",
" #display(_)\n",
" n_features = _.shape[0]\n",
" #plt.subplots(figsize=(10,20))\n",
" plt.barh(range(n_features), _['coef'], align='center')\n",
" plt.yticks(np.arange(n_features), _['features'])\n",
" plt.xlabel('Coefficient Value')\n",
" plt.ylabel('Feature')\n",
" plt.ylim(n_features,-1)\n",
" plt.show()\n"
]
},
{
"cell_type": "code",
"execution_count": 25,
"id": "infectious-magnitude",
"metadata": {
"execution": {
"iopub.execute_input": "2021-03-21T20:50:12.117101Z",
"iopub.status.busy": "2021-03-21T20:50:12.116908Z",
"iopub.status.idle": "2021-03-21T20:50:12.119162Z",
"shell.execute_reply": "2021-03-21T20:50:12.118681Z",
"shell.execute_reply.started": "2021-03-21T20:50:12.117080Z"
},
"tags": []
},
"outputs": [],
"source": [
"#compute_class_weight('balanced',classes=[0,1],y=y_train)\n",
"#compute_sample_weight('balanced',y_train)"
]
},
{
"cell_type": "markdown",
"id": "sticky-lying",
"metadata": {},
"source": [
"# Models"
]
},
{
"cell_type": "markdown",
"id": "greek-sperm",
"metadata": {},
"source": [
"## Common GridSearch Params"
]
},
{
"cell_type": "code",
"execution_count": 26,
"id": "voluntary-dylan",
"metadata": {
"execution": {
"iopub.execute_input": "2021-03-21T20:50:12.120781Z",
"iopub.status.busy": "2021-03-21T20:50:12.120613Z",
"iopub.status.idle": "2021-03-21T20:50:12.123509Z",
"shell.execute_reply": "2021-03-21T20:50:12.123000Z",
"shell.execute_reply.started": "2021-03-21T20:50:12.120762Z"
},
"tags": []
},
"outputs": [],
"source": [
"# Common Grid Search Parameters\n",
"\n",
"grid_search_defaults = {\n",
" 'cv': 3,\n",
" 'scoring': ['f1', 'recall', 'precision', 'balanced_accuracy', 'accuracy', 'roc_auc'],\n",
" 'refit': 'f1',\n",
" 'return_train_score': True,\n",
" 'error_score': 0,\n",
" 'verbose': 3,\n",
" 'n_jobs': n_jobs,\n",
"}"
]
},
{
"cell_type": "markdown",
"id": "fundamental-proportion",
"metadata": {},
"source": [
"# [**RUN ALL ABOVE BEFORE ANY MODEL**]"
]
},
{
"cell_type": "markdown",
"id": "stock-castle",
"metadata": {
"execution": {
"iopub.execute_input": "2021-03-04T00:14:57.578603Z",
"iopub.status.busy": "2021-03-04T00:14:57.578330Z",
"iopub.status.idle": "2021-03-04T00:14:57.581278Z",
"shell.execute_reply": "2021-03-04T00:14:57.580576Z",
"shell.execute_reply.started": "2021-03-04T00:14:57.578578Z"
}
},
"source": [
"## Decision Tree"
]
},
{
"cell_type": "code",
"execution_count": 27,
"id": "christian-comfort",
"metadata": {
"execution": {
"iopub.execute_input": "2021-03-21T20:50:12.124522Z",
"iopub.status.busy": "2021-03-21T20:50:12.124381Z",
"iopub.status.idle": "2021-03-21T20:50:29.201225Z",
"shell.execute_reply": "2021-03-21T20:50:29.199978Z",
"shell.execute_reply.started": "2021-03-21T20:50:12.124503Z"
},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Fitting 3 folds for each of 15 candidates, totalling 45 fits\n",
"\u001b[1mEstimator:\u001b[0m\n",
"DecisionTreeClassifier(max_depth=16.0, min_samples_split=0.01,\n",
" random_state=2021)\n",
"\n",
"\u001b[1mBest Result (Suggested):\u001b[0m\n",
"\u001b[1m\t train valdn\u001b[0m\n",
"\t f1 0.41 0.40\n",
"\t recall 0.28 0.27\n",
"\t precision 0.78 0.77\n",
"\t balanced_accuracy 0.63 0.63\n",
"\t accuracy 0.89 0.89\n",
"\t roc_auc 0.82 0.80\n",
"\n",
"\u001b[1mParams:\u001b[0m\n",
"\t{'max_depth': 16.0, 'min_samples_split': 0.01}\n",
"\n"
]
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"image/png": {
"height": 459,
"width": 389
},
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# Model 1\n",
"# Using scaled training dataset\n",
"\n",
"params = {\n",
" 'max_depth': np.logspace(1,7,3,base=2),\n",
" 'min_samples_split': np.linspace(.01,.5,5).round(2),\n",
"}\n",
"gs_dt1 = GridSearchCV(\n",
" DecisionTreeClassifier(random_state=random_state),\n",
" params, **grid_search_defaults\n",
")\n",
"gs_dt1.fit(\n",
" X_train,\n",
" y_train\n",
")\n",
"plot_grid_search_results(gs_dt1, 'f1')"
]
},
{
"cell_type": "code",
"execution_count": 28,
"id": "raised-rates",
"metadata": {
"execution": {
"iopub.execute_input": "2021-03-21T20:50:29.203156Z",
"iopub.status.busy": "2021-03-21T20:50:29.202905Z",
"iopub.status.idle": "2021-03-21T20:50:29.418760Z",
"shell.execute_reply": "2021-03-21T20:50:29.417903Z",
"shell.execute_reply.started": "2021-03-21T20:50:29.203124Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"accuracy score: 0.85\n",
"f1 score: 0.33\n",
"recall score: 0.27\n",
"precision score: 0.42\n",
"balanced_accuracy score: 0.61\n",
"roc_auc score: 0.61\n"
]
},
{
"data": {
"image/png": 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gpqbAxTe8z8A9ZvDhu535123r0aVrLbsPmcIv74j86of9+L8Hs8LHsw+vzYQx5cbCwwFHTKLn+gt444W1mu9DSwnEGKeFEHYBLgQOBk4lS9BuAC6IMY6rF39tCGEqcBZZYjYFuIVsGZkp9WIfCCHsn9/7eGAWcD9wbozxw3qxL4cQdidLIo8EFpB1+54XY3yJldTqEsAQQjvgFLLMvC9ZNn4T8KsY44KWbJuWNGFMey75Xl8+eHONstef+Xc33ny+C7seMI3zrhtFm3xAwo2/3JA7r1qfe65bl6N+MgGAR+/uwfOPdGPLgbMZ+tcRrNElSwxffGwK53+nH9dfujFnXPERkP2WeMWZm9Cxcx1X/Xs4626U/Wex98FTOefb/bjuko04/7pRAMye2YZrzu/FBpvO4+qH46KE8+vHTeLUr2zOtRduzFX/Ho7Umqy38TzO/9MH9N/6s7LXv37MRPp9YQ733rge117ce9H5rXecwa/uiJzy89H8z/7Z7lWDvzqFgXvMYNi/12boyf2oq82qOndduwFX/vMdTr50NM8/2p0F89vw3MNr89zDay/1vN2+MoWe6y/gift68Mjd6zbDJ1blySaBpL5nSjHGm4GbG7g2DfhR/mrMve4E7mxk7KPAo42MfQXYvzGxK6o1jgH8I/A74FPg98AnwCXAX1uyUVrSP65blx/svQUj3+nMtrvNLBsz/LUsMdzvsCmLkj+ArxyVdSG9+8qai849eV93AE686JNFyR/AF/eZyfaDZ/DY/1ubaZ9mVcZXnu7CmBGd+PK3pyxK/gC2230W2w+eybP/6caMKVnsyHc603P9BRx47ORFyR/AZp+fS+/N5/L+G51ZMH+Vjj2RVspBx43nmofeYrMtP+PVZ8pX23bdfyp1dfCX3/Za4vybL3Tljee70nfLOfRcf/6iWIBbf7fRouQPYMyIzjz9rx50X2ch/Qc0XCVfq/tCTh06iulT2nH1Bb0bjJO0arWqBDAvyX4f+DswOMb4U7INk/9CNlDyqy3ZPi1273Xrsl6v+Vz2j/fZ55CpZWO6rr0QgIljllzn8tNx2QLo3XouXHRuwkcdaNuuQP8BS1c0+m45l7raGt57OUsY33qhCwDb7DprqdhtdplFXW0Nb72YxW6942xufu5dDjlxybGJ8+fWMOGTDnTpXkv7Dqtw/XlpJX3juAlM/KQjZxy2BY//o9wkRnjwjnW55X835rNZSw/NKP7C03nNrOv46Qd6cMeVGzJm5NKbDiyYn/0T0nmNuqWuFR1x6li6rl3LX367MTOntbpOJ62EOmqSvpRWa/tpLA56vDjGWACIMRZCCOcA3yHrT/9XSzVOi536m4/ZbveZtG0Ln5T5hwNgz4Om8dcrN+D2yzdgwz7zGLDzbD7+oCO/P7sX7TvUceAxkxfFtu9YoFAHtQtraNd+yYRsdj6+cEKeSI4dlY1B2rD30jvorJ+P/ftkZPlxSvPn1fDhu5246ZcbMXNqO0644JMV/ORSy7ry3D68OqwrdXU19Opbfoeqh+4s3w3bde0FfGGHmcyZ3WbRWL5hD/Zg2IM9lopt176OHfaaBsDo98v/jK/fax5DjprIuI868u+/2vUrVZLWlgAOBiaXTL8GIMY4NoQwnPLr5agFDNqzfLdvqXU3WsBl/3ifX57Um/O/02/R+S7dF/LLO0ewxfaLq339B3zGh+925tn/dGOvb0xbdH7+3BpefTrr5iomgjOnZsdyM4OLA+Jnl5mUUrsQvt5vAHV12W+aBx0/iUN/MGmpOKmSvfx00/eHP/7cMay5Vh3337ruoupeQ7510jg22GQ+Lz7Rjcnjyv9C9fVjJ9ChY4F7blh/ie5jrf5a+V7AVaHVdAHn26z0AkY0EDIK6B5C8NfMVmLuZ2249bIN+Gh4Z7bZdSaHnDiRHfedzuzpbbnyrE2YOKb9otiDvjeZtu0K/OFnvXjinu7MntGGMSM68osf9GF6Pp6v+H+HhQuz/+mU67otnps/d+n/9GfPbMuXD/+Urx83iQ17z+Pe69flijN7rcqlB6QWc/gpY/nSYZOZ8HEHbvlNr2XG7nPwZI48fSyzprflj+eXH9fXsXMt+31zMjOmtuWhO8t3RWv1lnonEKXVmr6jxT6IaQ1cL+6J1/Rff7VKXXP+xjz7n+5872dj+c3dI/j+hWO55C8fct51o/jo/U5c+v0+i2L7bTWHM38/mgVz2/Crk/tw8BYD+N7uWzJ5bHuO/Wk2I79j52wcUsdO2XHhgqV/+yyOb+pUZsxS17VrOf1/x3DSzz/h2sfeY8DOs/j37evwf//yPymt3r7z40/47hmfMH1KOy44dnNmzWi4c2j/b0/ix5d9yIL5NVxy4ueY8HH56t/OX5rGWt1qefKfPZk3Z+mKu6SW1Zq6gIvloPKDWhafLz8YRRWlthYe+8farL/JPL550sQlru32lenssPcM/vt4V0YP70jvzbO/2r2+MY0Bu8zihUe6MXNaW/psMZdBe83ggb9k1YW1180mjRS7fmfPaLvoXNHsGdk/ROXWRivVaY0Cx5w9jh8f1J/nHurG4K+t1J7bUkVq06bAqb8cxf7fnszUSe049zuB0e93bjD+qNM/4agfjc3W9zzhc7zxXNcGY3fadxoAwx5celkYrf6yvYBTdwE7jCCl1pQAzsmPHRq4Xvw11FV7W4Fpk9uxYF4bevWbR02Zn+nem8/lv493ZeInHRYlgAA911+4aJmYouGvZ/9gbdo/27Vj482y+PEfd6BXvyV/Xxj/cfafT/H8uNEdeP+NzgzYZdYSC0kDrNcrmzAyfUpr+jGRGqd9hzp+dvUIdtpvGuM/7sC5RwXGjmro9+cCp/xiNEOOmsSMqW05/5jNia91afDebdoUGLTHdKZNbsdbL7rws1SJWlMX8HSyjZIb6o/rVhKnCrdWt1rad6hrcDbuJx9m53vkFbx7r1+HQz6/1aJkr2j+vBpefKwrPdZbwGZfyH5H2CrfueON55b+B+qNZ7vQpk2BsF0W88S9a/OLE/vy1L1LVylGvpM9a6Mys4ml1q3A2VeOZKf9pjEqdubHB2+5jOQPvn/+xww5ahKTxrXnjG9uuczkD2CTfnPp0q2Wt1/qsmhSlaqPy8BUtlaTAMYY5wOjyXb/KKcv2QzhKQ1cVwXp0KnAjvvNYPxHHbnvhiUHiL/8VBdeeKQrm/afuyip2+wLc5g1rd2i7l7Idvz44896Mf3T9hz6PxMXLSa99c6zWG/j+Tx4W89FFT+AV/+vC688vRa7HDB9UbVvt69Mo03bAnddvR7TP108Tmn6p2254RcbUlNTYL9v+Z+UVi9fP2Yiux0wlU8+7MhZ3wpMmdhQxwrstO9UDj5+AtOntOOsw7bgo2V0ERf12yr7BWv4G2suJ1Krq+JewClfTshLq7X1bQ0DvhNC2DzGuGh/rhDCRkB/XAOwVfnBxZ8QX12Dq8/vxXMPd+NzW3/G2FEdee4/3ei0Rh1n/H70ou7hATvPZtevTOM/f+3JpLHt2ewLc3jnv2vy9n+7sMPeMzjw2MVrBrZtCz/85RguOrYvp+y/OXsfPJU5s9vw+D1r07XHQk44f+yi2E37z+PIH43n1ss25MS9t2C3IdNYuKCG5x7qxrTJ7TnunLGEbefUb7rUarXvUMfhp2Y/Ax++twYHfndi2bgHbl+PqZPa890zsrUwR77bmX0O/rRs7JP392DMiMWJ4YabZlXzZVUVJbWs1pYA/oVsweehIYTDYox1IYQa4JdkmwT+uUVbpxWy7kYLuOrfw7n9d+vz/CPdeOO5LqzVfSF7fH0qR/14wlLj9376h9H89cq5PPXP7rz1QhfW33Qex5/3CV//3uSllnzZcd8Z/OL2Edz2uw349x096LxmHTvtN4NjfzqWDTadv0Rs8Vn3XLcuD/2tJ23aFNh8mzn86Lcfs9N+M5r9+yCtSpt8bi7d8112djtgKrsdUH6nnmcfXpt5c2vou2X2C9B2u85ku13Lr+854p01lkgAi7v8TB7fvmy8qoNLt1S2mkIrq6mGEP4GfAt4EXgC2AXYnWx7uMOKO4Q04b4vf37zwvb/77rW9f2QWpP9e3+xpZsgrbbGbfgOAG+OerVFB8yFEF7u3LvL9uHiHZLeN174X+aMnvVKjHFg0htXqdZWAYSsAvg2cAxwOvARcAHwm6Ymf5IkKaX0y8DgRJCkWl0CGGNcAFyavyRJUoUpQPKZu1Z40rKDXpIkqcq0ugqgJEmqfOm7gJWSFUBJkqQqYwVQkiQlVSB9BdAxgGlZAZQkSaoyVgAlSVJahWYYA2gJMCkTQEmSlJjrAFY6u4AlSZKqjBVASZKUlAtBVz4rgJIkSVXGCqAkSUrOhaArmwmgJElKynUAK59dwJIkSVXGCqAkSUrOLuDKZgVQkiSpylgBlCRJaRWaYSFoK4pJmQBKkqSkCkDBSSAVzS5gSZKkKmMFUJIkJZd6JxClZQVQkiSpylgBlCRJybkMTGWzAihJklRlrABKkqSknAVc+UwAJUlSYs2wDqCTSpKyC1iSJKnKWAGUJElpFdJ3AdsHnJYVQEmSpCpjBVCSJCVVIP0yMBYA0zIBlCRJyRXM2CqaCaAkSao6IYSNgHeBC2OMV9S7thZwPnAwsCkwE/g/4KIY42v1YvcFHmngMRNijBvUi98ZuBQYSFbYfAw4O8Y4skwbPw8MBXYBOgLPAefGGF9Zkc9ajgmgJElKrpL3Ag4hdAH+AXQtc21NsmRvG7KE616gF3AI8OUQwr4xxmdK3jIgP/4JGF/vdrPq3XswWbI4FbgZ6AYcAewVQhgUYxxVErsl8AzZfI3byZLFo4BnQgiDY4z/XdHPXcoEUJIkVY0QQm+y5G/7BkJOIUv+rowxnlbyvj3IqnXXsDjpo+TPZ8cYpy/juTXAn4HPgEExxjH5+dvJksLLgENL3vJ7oAuwQ7HqGEK4BngBuBrYoREft0HOApYkSckVCjVJXymEEE4H3iRL8B5vIOxgsmrb+aUnY4xPAU8CW4cQNi65NAAYvazkL7cvEIAbislfft/HyBLAg0IIPfN29gf2A+4r7XKOMb4F3AYMCiFsu5znLZMJoCRJSqqQ7wSS8lVI06V8OjAaGAzc2kDMn4CfxRhnlLk2Lz92AQghtAW2BN5oxLMH58cnylx7AmgL7NbIWIA9GvHMBtkFLEmSqsWJwKMxxtoQwublAmKMN5Q7H0JYB9gdmA2MKp4GOgFzQgi3AnsDawOvAD+PMf6n5Bb98uOIMrcv3q/YphWJbRITQEmSlFwzLQOzRQjh5XIXYowDl/fmGONDK/Hs/wXWAq6JMRYrgcXxf4eRTdi4nWzCyEHAgyGE42OMN+YxPfPjtDL3LnYfd2tCbJOYAEqSJC1DCOE84Biy7uOflVzqTFaluz7G+KuS+M+TzSD+QwjhgRjjBKB9fnkeSyue65QfVyS2SUwAJUlSWs23F/B7jan0pRRCuIRsQsinwJAY49TitRjjTcBN9d8TY3wnhHAFcAFZNfBPwJz8cocyj+mYH2fnxxWJbRITQEmSpHryCR5/Ar4HTAS+FGN8ewVuUVysuW9+LCaO3YAJ9WKL3bnTy8TWVz+2SUwAJUlScskrgKtQCKEjcDfwNbJJF1+KMb5fJu7zwEbAYzHG+qMeO+fHuflxeH7sW/JnSs4BxDKx9dWPbRKXgZEkSUkVoBmWgVk18gWb7yBL/t4Gdi2X/OWuJVvDb7sy14pLuryUH4flx3LLt+wJ1AEvNjIWsjGGTWYCKEmStNgpZItBfwDsGWMcu4zYu/Pjz0MIi3pVQwi7ACeQTRApLgXzFPARcGIIoU9J7D5kiz7fE2OcBJDvC/wMcEgIYVBJ7FZk28G9tLL7AdsFLEmSkmumZWCaVd71W9wB5A3ghyGEcqHXxhjHk1UADwUOAF4LITwEbEI28WMecESMcSFAvvbgScB9wEv5FnBdgCOBycCZ9Z5xGvA08GQI4Tagliz5qwFOXtnPagIoSZKU2RJYJ//zwfmrnHuB8THGBSGELwHnAEeQVQ+nk+01fEGMcYmxfjHGB0II+wMXAscDs4D7gXNjjB/Wi305hLA7MJQsSVxA1u17XozxJVaSCaAkSUqu0ieBxBhvBm6ud+41WLE95/JFoS/KX42JfxR4tJGxrwD7r0h7GssEUJIkpVWoaYZ1ACs7oWxtnAQiSZJUZawASpKk5FrhHJCqYgVQkiSpylgBlCRJSRWgWcbsOQowHRNASZKUnn3AFc0uYEmSpCpjBVCSJCWXehkYu3/TsgIoSZJUZawASpKk5FLvBWwFMC0TQEmSlFahGbaCc1JJUnYBS5IkVRkrgJIkKT337q1oTUoAQwivNPF5hRjjwCa+V5IkSQk0tQK4bRPfZw++JElVIPUkEKXVpAQwxujYQUmSpFbKMYCSJCk9K4AVLWkCGELYHziWrIt47RjjeiGEI4F+wGUxxs9SPk+SJFWeAjXJl4EpUONagAkl68oNIVwLPAB8E9gM6JlfGgRcBDwWQuiS6nmSJElqmiQJYAjhROD7wP8D+gO/KLl8CXAjsCPwkxTPkyRJFazQTC8lk6oC+APgjRjjYTHGEZT8NcUYp8YYjwf+CxyW6HmSJElqolQJYAD+s5yYJ4E+iZ4nSZIqWKFQk/SltFJNAvkMWG85MRvlcZIkaXVnl21FS1UBHAYcHELYpNzFEEJ/4BvAM4meJ0mSpCZKVQG8BPgy8GII4X/JuoQJIewB7ACcDbQHfpnoeZIkqaLZbVvJklQAY4yvAAcDbYHLgG+T/c0/DvyGLPk7Msb4QornSZIkqemSLQQdY/x3CKE38HVge6A7MAt4A7gnxjg91bMkSVKFcwxgRUu6E0iMcQ7wt/wlSZKqlQlgRUu9FVx/4HBgG6ALMAV4CfhrjHFsymdJkiSpaZIlgCGEocCZZOMAS30LuDSEcFqM8bpUz5MkSRWqAKReu8+KYlKptoL7PvBT4D2yCmA/snUBtwVOAiYC14YQvprieZIkSWq6VBXAk4GPgMExxqkl5ycDb4QQ7gNeAc4D/pXomZIkqUIVrNhVtFQLQW8O3Fcv+VskxjgO+AcwINHzJEmS1ESpKoAfA2svJ6YDWVewJEla3VkBrGipKoC/Bb4dQhhS7mIIYSfgCOCqRM+TJEmVrFCT9qWkmlQBDCH8rszpycA/QwhPAM8CE8gWg94BOAAYBSxoUislSZKUTFO7gE9fxrW981d9/YHLgSub+ExJktRK1NgFXNGamgDulbQVkiRJWmWalADGGJ9K3RBJkrSaKJB+EogVxaRSbwXXCehBthtIccRmDdAe6Al8JcZ4YcpnSpKkStMcEzecCJJSkgQwhLAGcDNwEEtvBVefCaAkSVILSrUMzIXAocCnwH+AuWTbwj0EjCZL2yeSJYiSJGl1V0j8UlKpEsBvAGOAz8UYhwCPA+/FGL8SY9yMLEFcD+iU6HmSJElqolQJ4CbAP2OMs/OvXwZ2KV6MMV4KvAr8T6LnSZKkSmYFsKKlSgAXADNLvv4AWC+EsF7JuSfI9gyWJEmrOxPAipZqFvAIYEDJ18PJxv1tAzySn+tAtjOIJElSiwohbAS8C1wYY7yizPWjgR+RFa+mAncBF8QYZ5WJHQKcB2wFzAHuB86JMU4sE7szcCkwkCy1fQw4O8Y4skzs54GhZL2qHYHngHNjjK804SMvIVUF8B/Al0MIF4cQ1gZeJ/tmnR1CWDOE0Bc4DPgw0fMkSVKlKpB+L+CEVcAQQhey3KVrA9fPAW4hy5OuIstrfgQ8HELoUC/2cOBfZHMdriGbB3EM8GwIoXu92MHAk2SJ4s3AvcDXgBdDCH3qxW4JPEO2+cbfgduAnYFnQgg7rPinXlKqBPB3wEtk2e9BMcZ5+bm9yRLBD4D1yb4xkiRJLSKE0Bt4CtixgeubApeQVdsGxRh/mk9wvZQsAft+SWwX4A/ASGC7GONZMcZvAycA/cjyomJsDfBn4LP8vj+KMR4HDCFbQ/myek35PdAF2CPGeFKM8WRgV6AOuHrlvguJEsB88seuwBHAsPz0UOBs4C3gBeCHMcaVbrAkSap8NYW0rxRCCKcDb5INUXu8gbATyYbIDY0xLig5PxSYARxfcu5wsuTt8hjjjOLJGOONQASOCSEU10feFwjADTHGMSWxj5ENlzsohNAzb2d/YD/gvhjjayWxb5FVAgeFELZdkc9eX7KdQGKMtcCdJV8XgP/NX5IkSS3tdLL1iU8kG9u3d5mYwflxiW1vY4xzQwjPkQ156xZjnF4S+0SZ+zyZP2crsi7kZcU+AXwJ2A24rxGx3wf2AF4rc71RUnUBS5IkLVaZs4BPBLaNMT67jJh+wIQY48wy10blx81LYiHrAm5s7IjEsU3SpApgCGFKE59XiDH2bOJ7JUlSddsihPByuQsxxoHLe3OM8aFGPKMnDU9anZ4fu5XEzosxzmlkLMC0xLFN0tQu4Bm4Ko8kSVr9tAfmNXCteL5TE2NLz6eKbZImJYAxxj4r81BJkrT6qiHdxI3Se5JtM7vcSt9KmkO2dnE5HfPj7CbG0kD8ysQ2SbJJIKuDD97rxpAv7trSzZBWW4UFn7R0E6TVVqFgx1wiU2m4e7V4fnpJbKcQQsd8CbzlxRbPT1iB2OW1oUmcBCJJktJLvRD0qjMcWD+E0LnMtb5k6/C9XxIL0KeBWMiWgymN7Zs4tklMACVJUlqpZwCv2v2Ah5HlR7uXngwhdAJ2At4umSFcXPt4jzL32ZOsSvduI2PrgBcbGQvZQtVNZgIoSZK02O1ALXBRCKFjyflzybaO+3PJuXuBmcBZIYQexZMhhOPIlmm5PsZYl59+CvgIOLF027cQwj5kiz7fE2OcBJDvC/wMcEgIYVBJ7FbAUcBLK7sfsGMAJUlSeq10SGKMMYYQLiPbzezVEML9wBfItmx7BriuJHZKCOEssq1uXwsh3AVsDBxG1o07tCS2NoRwEtlCzy+FEG4n2+rtSGAycGa9ppwGPA08GUK4jSwpPYpsPszJK/s5rQBKkiQt6Rzgh2Rp7Glku3lcDgypP9kjxngt8G1gElliNhi4BdgzxjilXuwDwP5k3cLHA18F7gd2jTF+WC/2ZbJu6GFkSeLhZN2+g2OML7KSklYAQwjtyMqY2wI9YoxnhhC2BmbV/2CSJGn1lXoZmNRijDcDNzdwrQD8MX815l53UrId7nJiHwUebWTsK2QJY3LJKoAhhD3JtkL5F/AL4Mf5pcOA4SGEM1I9S5IkVbjWOQGkaiRJAEMI2wIPAmuQ9Xf/v5LLLwDjgV+HEL6W4nmSJElqulQVwIuBucDAGOP5wFvFCzHGfwFfBKawuCooSZJWZ1YAK1qqBHB34K4Y4+hyF2OM44C7yAZRSpIkqQWlmgTSieXvSbcQKLeqtiRJWp0UmmESiFXApFJVAN8F9gshlL1fCKE98GVWctsSSZIkrbxUCeB1ZN27N4cQepZeCCGsR7aqdn/gpkTPkyRJlaz17gVcFZJ0AccYrw0h7EK2QvWRZBNCCCGMAnqRJZr30sj1dCRJUitnl21FS7YOYIzxaOBbwCNk4wFryfbMGwYcF2M8OF9YUZIkSS0o6U4gMca7gbtT3lOSJLU+lb4TSLVzL2BJkqQqk6QCGEJ4pZGhhRjjwBTPlCRJFcwKYEVL1QW8bSNiPgKmJnqeJEmqVK4DWPFSzQJuaP2/zkA/4DxgR2BIiudJkiSp6Zp1DGCMcU6M8S3gcGAa8JvmfJ4kSaoQ7gVc0VbJJJB8+ZeHgQNWxfMkSZLUsKTLwCzHZkCHVfg8SZLUUqzaVbRUs4AHNHCpBugCfBX4BvBYiudJkqTKVQMmgBUuVQXwNZb9V11DtjvIOYmeJ0mSpCZKlQD+hfIJYAGYD7wH3BFjnJjoeZIkSWqiVAngn4BXY4xzE91PkiRJzSTVLOC/A3clupckSWrtXAamoqVKANcG3kl0L0mSJDWjVAngfcDBIYR1E91PkiS1VvlWcClfVgHTSjUG8ClgT2BkCGEYMAqYUyauEGP8SaJnSpKkSmXCVtFSJYBXl/z5y8uIKwAmgJIkSS0oVQK4V6L7SJKk1YEVwIrWpAQwhDASuCLGeCVAjPGppK2SJElSs2lqBbAP0D1dMyRJ0uqkJnEF0IJiWqm6gCVJkhYzY6toqZaBkSRJUiuxMhXA7iGETVf0TTHGj1bimZIkqdIV0ncBW1FMa2USwNPy14oorOQzJUmStJJWJhn7iGzBZ0mSpCVZsatoK5MA3hRjvCRZSyRJ0urDBLCiOQlEkiSpyjgeT5IkJZd8EoiSsgIoSZJUZZpaAbwYeDJhOyRJ0urECmBFa1ICGGO8OHVDJEmStGo4BlCSJKVVIH0F0IpiUiaAkiQpOSeBVDYngUiSJFUZK4CSJCk9K4AVzQRQkiSt9kIIjUlJ94oxPpnHHw9c10DcCzHGnerdfwhwHrAVMAe4HzgnxjixTFt2Bi4FBpKlyo8BZ8cYRzbu06w8E0BJkpRUDenHANaw0kXFhlYwWQ/4H2Ai8F7J+QH58dfA3HrvGVP6RQjhcOAOYCRwDbApcAywRwhhUIxxWknsYOARYCpwM9ANOALYK48dtWIfq2lMACVJUnoV1gUcY7yo3PkQwv35H4+OMY4vuTQAmBJj/Omy7htC6AL8gSz52y7GOCM//zBwA1lV8Iz8XA3wZ+AzYFCMcUx+/naypPAy4NCmfL4V5SQQSZJUlUIIxwBfBW6OMT5U7/LWwJuNuM3hQA/g8mLyBxBjvBGIwDEhhLb56X2BANxQTP7y2MfIEsCDQgg9m/hxVogJoCRJSqvQTK+EQghrAL8AZgFn17vWiyype6MRtxqcH58oc+1JoCfZuMDlxT4BtAV2a8QzV5pdwJIkqRqdDmwEXFpmokZx/F/7EMI9wK5AZ+BZ4PwY44slsf3yY7kJHKPy4+bA6yWxI5YT2+xMACVJUnI1zXPbLUIIL5e7EGMc2NibhBA6AKeQTe64qkxIMQH8AfAQcBPQHzgQ2DOEcGBJl3FPYF6McU6Z+0zPj91KYgGmNSK2WZkASpKk9CpsEkg9hwEbAH+OMU4qc70NMBr4WYzx9uLJEMIeZEu23BRC2CzGOBdoD8xr4DnF853yY/t655cV26xMACVJUmvx3opU+pbh6PxYdp2/GONQYGiZ80/lM3aPBvYgqw7OATo08JyO+XF2fixWCcvF149tVk4CkSRJydUU0r5SCSF0BfYERsUYX2rCLV7Jj33z41SgUwihY5nYYnfu9JLY0vPLim1WJoCSJKma7EfWFfuPhgJCCNvnCzaX0zk/FheHHp4f+5SJLSaJsV5s30bENisTQEmSlF7lLgFT3MLt6WXE3As8EUJYp8y14jItxerhsPy4R5nYPckqeu82MrYOeLHMteRMACVJUjXZLj/+dxkxd5PlSEPz3TsACCF8ExgCPB1jfCs/fS8wEzgrhNCjJPY4siVdro8x1uWnnwI+Ak4MIfQpid2HrDJ5TwOTUpJzEogkSUqvcmcB9wPmxBjHLiPmUuAA4ARgQAhhGNkOHkOAccCxxcAY45QQwllkewC/FkK4C9iYbKbxcEomk8QYa0MIJwH3AS/lE0q6AEcCk4Ezk33K5bACKEmS0ko8AaQmbTdwT2DMsgJijNOAXYArgA2BU4GBZHv7DowxjqwXfy3wbWAScDLZjh+3AHvGGKfUi30A2J+sW/h4sq3o7gd2jTF+uHIfrfGsAEqSpKoRY+zayLhpwI/yV2Pi7wTubGTso8CjjYltLiaAkiQpvcrtAhZ2AUuSJFUdK4CSJCm5lIs3Kz0TQEmSlJ4JYEWzC1iSJKnKWAGUJElJ1ZC+C7gGi4opWQGUJEmqMlYAJUlSWun377X8l5gJoCRJSs+EraLZBSxJklRlrABKkqTkXAewslkBlCRJqjJWACVJUnpWACuaCaAkSUqupmAGWMnsApYkSaoyVgAlSVJargNY8awASpIkVRkrgJIkKTmXgalsVgAlSZKqjBVASZKUnhXAimYCKEmSkrMLuLLZBSxJklRlrABKkqT0rABWNCuAkiRJVcYKoCRJSqqmkH4MoGMK0zIBlCRJ6ZmwVTS7gCVJkqqMFUBJkpScXbaVzQqgJElSlbECKEmS0itYAqxkJoCSJCk5u4Arm13AkiRJVcYKoCRJSqtA+mVgrCgmZQKoVWrtnvM44oTh7LDrJLr3mMesGe157cV1uO1PmzN+7BqL4jp2Wsih3xnJ7vuNY70N5jBlcieefmRD7rypH/PmLvmfbdu2dQw5dDRf/vrHbLDxHGbOaM/zT63PHdf1Z8b0Dku1YeNNZ3HUie+zzaBPad+hljGju3DP7X15+pGNmv3zSy1lrbUXcsxZ49npS9Pp1rOWTye04+n7u3Pbbzdg3pzFnUEdO9dx5I/Gs8eB0+m5wQJmTGnL84905eZfb8iMKUv+7LVrX8ehP5jE3odMZcNN57Ngfg3xtTX46+/X543nuqzqjyhpBdgFrFVm7Z7z+N1Nz/CVgz/m4w+78M+/9WH4293Z48tjufyWZ9hok9kAtGlbx0WXv8QRJ3zAlMmd+NfdvRk3Zg2+dewIfv2n52nfoXaJ+/7ogjc48SfvMn9+Wx74+6YMf7sbQw4dzRW3PEPXbvOXiO0XpnP5zc/yxd0n8OKwdXnk/k3o0XMeZ//iNQ781oer7HshrUqd1qjld/d+wFe/+yljRnTi3hvWYcqE9hx20iR++bcRtGmblVZqagr8/LaRfOuHk5g+pS333bgOH77XiSHfmcLl973PGmst/tmrqSlw8S0fcuw546ldWMO//tKTZ/7djS0Hfsav7hrB7l+d1kKfVpWipi7tS2m16gpgCGEj4F3gwhjjFS3cHC3HEScMZ70N5nLdFVtw7x2bLTq/55c/4cxLX+f4097lkjMG8aWvjWHAwCncc0cfrr/i84vivnvSexx2zEi+dODHPPD3PgBst+Mk9jpgLMMe24BfnrMdUAPA/t/4iFPOeYtDjx7BjVdtCWT/YJ1+wRu0bVvgpyfuxPvvdgfgjuv684c7/o/vnjScf9+zKQvmt10l3w9pVRnynU/ZtP887rluHa69cOP8bIGzrvqIfQ6Zxt4HT+XRu3uw6wHTGbDzbIY92I2fn9CbQiH7eTr2p+P49qkT+cYJk7j9dxsAMPjAaQzacxbDHujGL37Qm7raLPauP87lygff54dDP+H5h7uyYL51BqkStdqfzBBCF+AfQNeWbosaZ+c9JjBtSgfu+2vfJc4/+dDGjP14DbbfaTI1NQU22mQ206d24O5b+i0R99TDWRftlltPW3Ru076zmPppB+7+y2YUk78sdkMAtiiJ3Xr7KWzWfyb3/rXPouQPYNbM9tx67eY88e+N6L72khVDaXWw+bZzAHjobz1Kztbwnzt6ArDl9p/lcdnxkbvWXpT8ATx425JxALsdMB2Av1y2/qLkD+DjDzrx1D+7032dhfTfZk76D6PWo5D4paRaZQUwhNCbLPnbvqXbosZp06bAXTf3o3ZhmyX+YSlasKAN7TvU0a59HTdeteWiql2pXn2yLuKpUzouOnff3/py39/6LhW7Se8sdtqUxWMAB+4yCYBnHt9gqfjHHujFYw/0WsFPJbUOM6ZmVe31es3nw3c7Lzrfc4MFAEzPx/bNmNpuUVypnhvmcZ8u/ifjqfu78/GIjowZ0Wmp5y2Yn/2Md16jdqlrqh4uA1PZWl0CGEI4HbgEWAN4HNi7RRukRqmrq+Gfdy6dqAH06j2LXr1nMfbjNcp2v3bpOp+BO0/ixJ+8w6wZ7Xjg75s2+JzOay5g6+2mcOJP3mHB/Dbcc/virubem80EYNwna3DU94ez11c+oUfPeYwZvSZ/u/FzPPP4hiv5KaXK9NBfe7D/4VP4wUVjmTmtHSPe6kzY9jO+97NxzJrehof+mlUGn7y3O4efOoEjfzSBcaM68sZza7LJ5+Zx2q/HMH9eDf+8ueeiew57oDvDHui+1LPata/ji3tnP2sfvb90ciipMrS6BBA4HRgNnAhsjglgq1ZTU+B/znybtm3hP/dustT1Lx34Maed9yYAcz5ry/mn7sD4T9Yse69tdpjM0D++CEDtwhp+fd62vPvm2ouu91x3LvPnteHcX77K57acznNPrk+hUMOue43n3F+9yh9/PZ8H/1/vZviUUsv64M01OOfbm3HO1aO5/L4PFp2fMKY9P/56fyaMySrlk8d14IyDP8c5V4/m57ctnhQ1c2pbzvnWZsRXy//slfrWKRPZYNP5vPjYWkwau/QsfFWJAul3ArGimFRrHAN4IrBtjPHZlm6IVlaBH57zFtt+8VOGv9NtqbGBADOmt+cft/flif9sRNu2BS698r9sv9OksndbML8N9/61Dw//sxdz57blrJ+/xr5Dxiy63rFTLR061tHnczM55cjduPIXA7hq6NacevSuzJjenuNPe5fuPeY126eVWkq3ngs49pxx9Fh/Ic893JW/X7surz+zJuv3WsCpv/mYNbtmXbUdO9fynTPG0zvM47VhXfj7tevy/CNdWbNbLaf+ZgzrbrzsMbL7HjqFo348gVnT2/CHczdeZqykltXqKoAxxodaug1aeW3a1nHquW+y39c+YdyYNbj0jIEsXLj07yPPP7UBzz+Vjdm7J0znsuuf4ycXvc5xB+251HqA77zeg3dez7qy7ri+P7+/5Rl+eM5bvPrfnnw6sfOisYd337IZkycuHgc1cdwa/PPOPhz1/ffZcfcJPHRfw13MUmt0ztUfsdUXP+MXJ/bm6fu7Lzr/jRMm8YOLx3L6bz7mFz/ow/9cOpZdD5jB9T/fkLuvXm9R3K4HTOOCG0Zz/p9HceqQzcs+44AjPuWUX49hwbwaLvleXyZ83LFsnKpDDenHAC49elwrozVWANXKdexYywX/+zL7fe0TPvloDc75nx2ZMnn5Y4VGxG48/u+N6d5j/hIzgcuZNL4z9/2tD+071DFw58kAzJ6VJYwfvNdtqfgPh2eTyTfs9dlS16TWbJ0N57Pd7rN447k1l0j+AO65bl1Gx47sOmQ6a6xVyz4HT2X8Rx24++p1l4h75t/defGxtQjbzWHT/nOXesZRPxnP6ZeNYf7cNlx4TF9ef9ZFoIWzgCucCaBWqS5rLWDo1S+ww26T+OC9rpx5ws5MmtB5iZgvbDeFnQZPKPv+ieOz2K7ds66oz205jT2+NLZ87Lgstlu+GPTYj7PxS+3aL72iaNt22bl5c10DUKuXdTfKZvB+3MCEjNHDO9G2LfTefC4dOhUYM6Ij5Woto4dn719viW7gAqf+agzf+ckEZkxpy9mHbcar/7dW6o8gqRm0ui5gtV7tO9Ry4e9eYoutp/HGyz245IyBzJndfqm40372ButvNIcj99+HWTOWHES+Wf8ZAIwbk20bd8xJke12/JRRI7owesSSS0L2LcZ+ksW+/dra7LX/WLYZ9ClvvLTOErH9t8zWNPvwA//x0upl6qTsf/Mbb1Z+fOvGm82jrg4mjOnA/Hk1Dcf1zc5PmbT4Z/b7F45lyNGfMmlse849fDNn/WoJlboMTAjh58DPGrh8Z4zx2yWxRwM/Ipt0OhW4C7ggxjirzH2HAOcBWwFzgPuBc2KME8vE7gxcCgwkq28+BpwdYxy5Eh9thVgB1Crz3ZMin99mKu++0Z0LT9+hbPIHMOyxDWnXrsB3T4pLnN9h14nsstd4Pnx/Ld5/N+vG/b9Hs6Vbjj050qbN4v/bfG6L6Qz55mimftqB/z6z7qLYWTPaceBho9mkz+Kf3Y02mc1XDvmIKZM78tKzS3Z9Sa3d+I86Mvz1zgzYZRY7f3n6Ete+fPin9PvCXF5+ci2mTGjPC490ZcPe8znwuCUnWm0/eCY77jeD0cM7MvLtLMnb6UvTOeTEyUyf0pYzD+ln8qfWZAAwD7i4zOvvxaAQwjnALWS50lXA62TJ4MMhhCWqEyGEw4F/AesB15AtU3cM8GwIoXu92MHAk2SJ4s3AvcDXgBdDCH2SfcrlsAKoVWLtnvP46qEfAfDxqC4cevSIsnF339KPu2/pxw67TeQrB39M38/N5J3X12ajTT9jx90nMHNGe/73/G0pdlE9cv8m7LbPeHbYbRJX3jqMV19Yh57rzmWXvSZQW1vDb87fdtFkkVkzOnDVL7fmrEtf43c3PcPTj2xEoQ5222c8HTvVctkF27BwgV3AWv1c/pNN+M3fR3D+9aN44ZGujBnRkb5bzmWHvWfy6fh2XHVONmP32gs3Imz3GSf/fCw7f2kGH7zZmY36zGfn/acz97M2XHbaphR/9r571ngARr7dmX0OnVr2uU/d152PPzAxrE6F9MvApBsIOAB4J8Z4UUMBIYRNydYcfg7YI8a4ID9/CXA+8H3gD/m5LvmfRwLbxRhn5OcfBm4gqwqekZ+rAf4MfAYMijGOyc/fDjwCXAYcmuqDLosJoFaJsNVU2nfIxtl96cAxDcbd99e+zJ7VnrNO2Jkjjn+fXfcez4HfHsXM6R149F+9uOO6/kuMGayrq+HiHw/ikKNHsvcBn/C1b43is9nteP7p9bjj+v58NHLJLt1hj23Ip5M6cvj3PmDwvuMAGP5ON+64vj9vv9YDaXU08p3OnHJAf4780QS232MmX9xnBlMnteeBW3tw2283YMrErBo/eVyHLO7HE9hpvxkM2HkWM6e146n7unPb7zbgk5HZzN411qpls89nk0G2230W2+2+VG8YACPe7mwCWK0KzdAFnOB+IYSuQG+yCtyynEiWIw0tJn+5ocBpwPHkCSBwONADuLCY/AHEGG8MIZwFHBNCODvGWAvsCwTgt8XkL499LITwCHBQCKFnjPHTlfmcjWECqFXi+ac2YMgXv9Lo+DmfteOGK7fkhiuX3hKuvoUL23DnjZ/jzhs/16h7v/tGDy447YuNbou0Ohg3uiOXnb78JY6mTW7PH8/txR/PbTjms5lt+fJG2yRsnbTKDMiPbywnbnB+fKr0ZIxxbgjhOeDLIYRuMcbpJbFPlLnPk2TJ5FZkXcjLin0C+BKwG3Dfctq30kwAJUlSepU5CaSYAK6TV9wG5V8/BvwsxlgcfN4PmBBjnFnmHqPy4+bAf/NYyLqAlxX7eklsuXFQpbHNrlUngDHGm8kGUEqSpNXfFiGEl8tdiDEObMT7iwngmcA/gevyc4cA+4YQ9owxvgb0BD4sewcozqYqLirbE5gXY5zTyFiAaY2IbVatOgGUJEmVqUKXgakFRgPHxBifLJ4MIRwJ3AbcCGwPtCebKVxO8XxxgOuKxpaeX1ZsszIBlCRJrcV7jaz0lRVjPBk4ucz520MI3wcGhxAC2Tp+HerH5Yr7HM7OjysaSwPx9WOblesASpKk9OoKaV/N75X82Jds0eeGumKL54tdtlOBTiGEchtgl4stPb+s2GZlAihJktJKvQ9wgv2AQwjtQgg7hBB2bCCkuMbYXGA4sH4IoXOZuL5AHfB+/vXw/NingViA4uSS4fXOLyu2WZkASpKkatAWeAb4dwhhiVX/8wWadwEWAq8Bw8hypN3rxXUCdgLeLpkhPCw/7lHmmXuSVfTebWRsHfBiIz/PSjEBlCRJydUU0r5WVoxxHtn+vGsDP613+SfA1sAdMcZpwO1kE0Yuqte1ey7QlWw3j6J7gZnAWSGERTsKhBCOI1vS5foYY11++ingI+DE0m3fQgj7APsB98QYl9yLsZk4CUSSJFWLn5BV+n4eQtiTbG2+gWTVt3eBHwPEGGMI4TLgbODVEML9wBeAIWRVxOuKN4wxTsl3/LgGeC2EcBewMXAYWZfv0JLY2hDCSWQLPb+UbwHXBTgSmEy2PM0qYQVQkiSlVyikfSUQYxxFtvjzjWS7c5xKNvbut8DO9bZgOwf4Idnow9Py+MuBIXk1sfS+1wLfBiaRzTIeDNwC7BljnFIv9gFgf7KE83jgq2SVyV1jjA2tPZicFUBJkpRUDenXAaxJdJ8Y4yfA9xoRVwD+mL8ac987gTsbGfso8GhjYpuLFUBJkqQqYwVQkiSlV5k7gShnBVCSJKnKWAGUJElpFaAm0cSN0nsqHRNASZKUXt3yQ9Ry7AKWJEmqMlYAJUlScsm7gJWUFUBJkqQqYwVQkiSlZwGwolkBlCRJqjJWACVJUloJ9+9d4p5KxgRQkiQll3ovYKVlF7AkSVKVsQIoSZLSs8u2olkBlCRJqjJWACVJUnI1bgVX0UwAJUlSWgWaYRZw2ttVO7uAJUmSqowVQEmSlJ4Vu4pmBVCSJKnKWAGUJElJ1QA1iccA1iS9m0wAJUlSeq4DWNHsApYkSaoyVgAlSVJaBSD1OoAWFJOyAihJklRlrABKkqTECskngVgCTMsKoCRJUpWxAihJktJzFnBFMwGUJEnpmQBWNLuAJUmSqowVQEmSlJbLwFQ8K4CSJElVxgqgJElKLv0yMErJBFCSJKVnAljR7AKWJEmqMlYAJUlSYoVmqABaUUzJCqAkSVKVsQIoSZLScwxgRTMBlCRJabkOYMWzC1iSJKnKWAGUJEnJuQ5gZbMCKEmSVGWsAEqSpPSsAFY0K4CSJElVxgqgJElKr84KYCUzAZQkSWkVCqRft6UANSt3hxDCBsBFwBBgfWAK8ChwQYxxZEnc8cB1DdzmhRjjTvXuOwQ4D9gKmAPcD5wTY5xYpg07A5cCA7MPxWPA2aXPXxVMACVJ0movT/5eBDYBHgH+BgTgCOCAEMJOMcb38/AB+fHXwNx6txpT776HA3cAI4FrgE2BY4A9QgiDYozTSmIH58+eCtwMdMufv1ceOyrBR20UE0BJkpRe6kkgK1n9I6v8bQL8JMb4u+LJEMKRwG3Ab4ED89MDgCkxxp8u64YhhC7AH8iSv+1ijDPy8w8DN5BVBc/Iz9UAfwY+AwbFGMfk528nSwovAw5d6U/ZSE4CkSRJ1eAbwCTgitKTMcbbgRHAl0MIxbxoa+DNRtzzcKAHcHkx+cvveSMQgWNCCG3z0/uSVRxvKCZ/eexjZAngQSGEnk34XE1iAihJktIrFNK+VkKehA0FLooxltukbh7QAegQQuhFltS90YhbD86PT5S59iTQk2xc4PJinwDaArs14plJ2AUsSZLSSz0LeCVKVjHGWuD35a6FELYAtgBGxBjnhhCK4//ahxDuAXYFOgPPAufHGF8seXu//FhuAseo/Lg58HpJ7IjlxK4SJoCSJKm12CKE8HK5CzHGgSt6s7zL9w9k6eWf89PFBPAHwEPATUB/svGBe4YQDowxPpTH9ATmxRjnlLn99PzYrSQWYFojYpudCaAkSUqrUIBCuZ7Wlbznyk8EWSSflPEnYB/gJRaPDWwDjAZ+lo8PLMbvQbZky00hhM1ijHOB9mTdx+UUz3fKj+3rnV9WbLMzAZQkSa3Fe02p9NUXQmhHts7fMWTdt1+PMc4HiDEOJRsvuIQY41P5jN2jgT3IqoNzyMYOltMxP87Oj8UqYbn4+rHNzkkgkiQpvQqaBFIqhLAGcB9Z8vc+sFeMcWwj3/5KfuybH6cCnUIIHcvEFrtzp5fElp5fVmyzMwGUJEnp1RXSvhIIIawNPA58BXgV2C3G+FG9mO3zBZvL6Zwfi4tDD8+PfcrEFpPEWC+2byNim50JoCRJWu2FEDoB/wJ2BJ4C9iy3VRtwL/BECGGdMteKy7S8lB+H5cc9ysTuSVbRe7eRsXVkO5WsEiaAkiQpvcrrAh4K7AI8BxxQunBzPXeT5UdD84kiAIQQvkm2h/DTMca38tP3AjOBs0IIPUpijyNb0uX6knUHnwI+Ak4MIfQpid0H2A+4J8Y4aWU/ZGM5CUSSJK3W8n2AT86/fBc4O4RQLvRXwKXAAcAJwIAQwjCyHTyGAOOAY4vBMcYpIYSzyPYAfi2EcBewMXAYWZfv0JLY2hDCSWTjD1/KJ5R0AY4EJgNnJvvAjWACKEmS0iqQfi/glbvdTiyefXvcMuKuiDFOCyHsAlwIHAycSpag3QBcEGMcV/qGGOO1IYSpwFlkSeYU4BayZWSm1It9IISwf37v44FZwP3AuTHGD1fqE64gE0BJkrRaizHeywqsIhhjnAb8KH81Jv5O4M5Gxj4KPNrYtjQXE0BJkpRY2qVbFt1TyZgASpKk9OoS7wSipJwFLEmSVGWsAEqSpPSSdwErJSuAkiRJVcYKoCRJSqvyloFRPSaAkiQpsXT79y5xTyVjF7AkSVKVsQIoSZKSKxRcBqaSWQGUJEmqMlYAJUlSWgXSjwF0CGBSJoCSJCk91wGsaHYBS5IkVRkrgJIkKbFCM+wFbEUxJSuAkiRJVcYKoCRJSs8xgBXNCqAkSVKVsQIoSZLSKkAh9RhAC4pJmQBKkqTECs3QBWwGmJJdwJIkSVXGCqAkSUov9U4gSsoKoCRJUpWxAihJktIqAAUngVQyE0BJkpRcwS7gimYXsCRJUpWxAihJkhIrpO8Ctg84KSuAkiRJVcYKoCRJSqpQSD8G0K2F0zIBlCRJ6SXvAlZKJoCL9VlQM4sxHZ9p6XZIq63CJgtaugnSamtBh7nUFCpjZNfCDnMZt8n7ye+pdEwAF5tRqKljfs2MUS3dEGm11amlGyCt1voUqJ3R0o0A3iu0KbCg05xmuXdz3LQa1RTsVJckSaoqlVErliRJ0ipjAihJklRlTAAlSZKqjAmgJElSlTEBlCRJqjImgJIkSVXGBFCSJKnKmABKkiRVGRNASZKkKmMCKEmSVGVMACVJkqqMCaAkSVKVadfSDZBWVAihHXAKcALQFxgH3AT8Ksa4oCXbJq1OQggbAe8CF8YYr2jh5khKyAqgWqM/Ar8DPgV+D3wCXAL8tSUbJa1OQghdgH8AXVu6LZLSMwFUqxJC2AX4PvB3YHCM8afAYOAvwCEhhK+2ZPuk1UEIoTfwFLBjS7dFUvMwAVRrc3J+vDjGWADIj+cABeD4lmqYtDoIIZwOvAlsAzzesq2R1FxMANXaDAYmxxjfKj0ZYxwLDAf2aJFWSauP04HRZD9rt7ZsUyQ1FxNAtRohhI5AL2BEAyGjgO4hhHVXWaOk1c+JwLYxxmdbuiGSmo+zgNWa9MiP0xq4Pj0/dgMmNXtrpNVQjPGhlm6DpOZnBVCtSfv8OK+B68XznVZBWyRJarVMANWazMmPHRq43jE/zl4FbZEkqdUyAVRrMh2oI+viLadbSZwkSWqACaBajRjjfLLZiX0bCOlLNkN4yqprlSRJrY8JoFqbYcAGIYTNS0/mW1b1B55rkVZJktSKmACqtflLfhwaQmgDEEKoAX4J1AB/bqmGSZLUWpgAqlWJMT4K3AkcAjwXQvgV2ZZVR5NtD/dACzZPkqRWwQRQrdF3gAuAdch2Ldgg//qo4vZwkiSpYTWFgv9eSpIkVRMrgJIkSVXGBFCSJKnKmABKkiRVGRNASZKkKmMCKEmSVGVMACVJkqqMCaAkSVKVMQGUJEmqMiaAkiRJVcYEUJIkqcqYAEqSJFWZdi3dAKlahBAuAi4sc2khMAN4E7g+xnjbKmxTd2Aq8FSMcc/83DHATcCPYoxXNOGehwMvxBhHJmtodt/XgG1ijDXLiXsS2ANYO8Y4bQWf0Qf4ELgvxnhQU9q5jHuPArrHGLunvK8kNYUJoLTq3Qe8VvJ1O2A94DDg1hDCFjHG81qiYbnXgIuB51f0jSGEXwNnAdslbpMkKSETQGnVuzfGeHP9kyGE/wVeBX4aQrguxjh6lbcMiDG+xpIJ6opYP11LJEnNxTGAUoWIMb4P3Au0Bb7csq2RJK3OrABKleWT/NgTlhiPdxhwPNnYtgnAXjHGkSGErsC5wDeBXsBk4J/AhTHGiaU3zse3/RzYD1gDeAS4qH4DGhoDGEIYkD9rT2BN4H3gD8BNMcZCPsatdx7+aghhdIyxT/7eGuBE4PvAlsBc4P/ydr5a7/mdgfOBI8gqiq+TdSs3WQihPXAScHj+/M7AOODfwPkxxkll3nMwWVd4f+Ajsu/JZTHGBfXiPkf2fdwP6A6MBP5SLlaSKoUVQKmyfC4/flLv/FXAusCVwH/z5K8b8AxwNtnEhd8Dz5ElWS+GEDYsvjmE0At4liypeg64EdgKeKgxjQoh7E02JvBg4GngT2RJ1A0sTiKvIEvWyK9fUXKLW4BrgA7AtcDdwGDg2fzexee0IUvKziFLdK8BFgAPA5s2pq0N+GvengXAn/P2zSVLSh8sE79z3sYReRvqgKHAraVBIYTtgZfIEvDHgcuBKXnsP0MIbVeizZLUbKwAShUihDAIOBCYQ5YElVoA7BZj/Kzk3FCyJO7kGOPVJfc5kGyiye/JKocAvwA2BI6JMd6Sx50L/AvYYDntagtcD9QAe8QYn8vPnwe8APwshPDHGOMVIYRtgW2Aa/OxhIQQvgl8B7gD+G6McWF+/pdkydNfQgibxRjnA98lq3LeCJwQY6zLY38DnLnMb2DD7d8JOAS4PcZ4VMn5dsArwKAQwuYxxuElb1sPOC3GeGW979W3Qgg3xBgfyauatwAdgV1ijC+X3Pt3wI/IEsyrkaQKYwVQWvUOCiFcVPL6RQjhbrIu0XbAGWW6JB8sTf7y5OVo4O3S5A8gxvhPssrgwSGEriGEDmSVu7eLyV8eNxv4aSPauxPQF7i1mPzl758L/IRsaZtOy3j/9/Lj6cXkL3//h2TVtY3Juk8h66ItAOcUk7/c+cD0RrS1nDHAMcAFpSfztgzLv1yv3ntGAH8siZ0D/Cz/8sj8uCNZAn5DafJX0t75wLFNbLMkNSsrgNKq9/X8VbSAbOzew8AfY4wPl3nPqHpfB6AL0DZfX7C+TmSTSbYm65LsQlZtq++l/PnLsk1+fK7+hRjjo8Cjy3n/QLLu1pNDCPWvbZEftwUeyJ/1Uf3xizHGeSGEl4G9WUExxjHALSGEdnmXbQD6kS1Vs28eVr+r9vkYY229cy+TdQUXvx8D82O/Bv4OZgLbhBBqYoyFFW23JDUnE0Bp1Tu23DIwyzGn3tfd8+MWlF9cuqgHWUUNsoRkCTHG2hDC8ipra+fHGcuJa0h3sv/XLK+dxWdNbCBmShOfTwjhRLIK4Eb5qWlkYxrfJavk1V9cekL9e8QYF4QQ5pIl07D472D//NWQLpT53ktSSzIBlFqnWfnx1hjj0csKDCFsmf+xW5lrNWQzehvzrLXKvL89UJOP31vW+2fGGBsziWNquXbmujRwfpnyMYjXAm+QzQR+Jcb4cX7tGrIEsL7uZe7TlWz2dDERLX5fvhdjvLEpbZOkluIYQKl1isA8YGCexC0hhHB6COG8EEJP4AOy8XO7lLnP58lm8y7Lm/nxi2WuHQbMCSF8J/+6XFfnG0CvEMJSk01CCF8NIfw8hFDsVn0Z2CSEsGm9uLY0fXeRI4rHGON9xeQvV0yO638Pdyhzn+L3rzje7438OKh+YAihfQjhtyGEU5rSYElqbiaAUiuUT8C4kyyB+3HptRDCnsBlwHHA1HwtujvIxqr9uCSuA/DLRjzuaeBj4Oh8lm/x/R3zZ9eRLYECi8cTdih5/81kCdYf8mcW378h2SSQc1hcTbs5P/4ury4WnUnTdxmZmx+XeH8I4WiyGccA7VnS1nnlsBjblWwNxUJJG58mW37neyGEneu9/6dk35uBSFIFsgtYar3OIKtKXRZC+DrZkiy9yGb8LgCOK5lJ+zNgH+C3IYQvA++QTYDoweIEqawY48IQwnFky6A8G0L4B9k4va+SLZL8oxhjcd3C4vG3IYRHY4wXkyVMB5ItxfJmCOEhsv/3HEa24PVPY4wj8mfdFUI4lGxdvZdDCI8BXyCb/DGaxQtNr4jbgG8D94QQ/ko2lvGLZMnfRLIZwD3rvWcEcEcI4RvAJOBrZDOhfxVjfDFva22eRP4HeDqEcF/+vkF5ez8kS24lqeJYAZRaqXypmB2B35ItpXIqsDtwP7BTjPHJktipwK5kY+G2JlufbjxZUjivEc96NH//o8AQ4GRgNtm6fleUhP6RbIeRQcCpIYQu+QzYQ4HTgM/IdjT5FlkS+o0Y46/rPe5wssWtOwH/Q7ZO4Tdo4v7EMcYHyBLAEcBRZEvCdMo/Q3Hyxlfqve1feTsHAT/I231CjHGJhC7GOIwsmbyb7Ht/GlmSeiWwc4xxXFPaLEnNraZQcHUCSZKkamIFUJIkqcqYAEqSJFUZE0BJkqQqYwIoSZJUZUwAJUmSqowJoCRJUpUxAZQkSaoyJoCSJElVxgRQkiSpypgASpIkVRkTQEmSpCpjAihJklRlTAAlSZKqjAmgJElSlTEBlCRJqjImgJIkSVXGBFCSJKnK/H+m9vEWCp+bpQAAAABJRU5ErkJggg==\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {
"image/png": {
"height": 261,
"width": 320
},
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"score_classification_model(gs_dt1, X_test_mms, y_test)"
]
},
{
"cell_type": "code",
"execution_count": 29,
"id": "reflected-hardware",
"metadata": {
"execution": {
"iopub.execute_input": "2021-03-21T20:50:29.420173Z",
"iopub.status.busy": "2021-03-21T20:50:29.420006Z",
"iopub.status.idle": "2021-03-21T20:50:53.502973Z",
"shell.execute_reply": "2021-03-21T20:50:53.502028Z",
"shell.execute_reply.started": "2021-03-21T20:50:29.420131Z"
},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Fitting 3 folds for each of 15 candidates, totalling 45 fits\n",
"\u001b[1mEstimator:\u001b[0m\n",
"DecisionTreeClassifier(class_weight='balanced', max_depth=16.0,\n",
" min_samples_split=0.38, random_state=2021)\n",
"\n",
"\u001b[1mBest Result (Suggested):\u001b[0m\n",
"\u001b[1m\t train valdn\u001b[0m\n",
"\t f1 0.43 0.43\n",
"\t recall 0.57 0.56\n",
"\t precision 0.35 0.34\n",
"\t balanced_accuracy 0.70 0.69\n",
"\t accuracy 0.79 0.79\n",
"\t roc_auc 0.78 0.78\n",
"\n",
"\u001b[1mParams:\u001b[0m\n",
"\t{'max_depth': 16.0, 'min_samples_split': 0.38}\n",
"\n"
]
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"image/png": {
"height": 459,
"width": 389
},
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# Model 2\n",
"# Using scaled training dataset, balanced class weight\n",
"\n",
"\n",
"params = {\n",
" 'max_depth': np.logspace(1,7,3,base=2),\n",
" 'min_samples_split': np.linspace(.01,.5,5).round(2),\n",
"}\n",
"\n",
"gs_dt2 = GridSearchCV(\n",
" DecisionTreeClassifier(random_state=random_state, class_weight='balanced'),\n",
" params, **grid_search_defaults\n",
")\n",
"gs_dt2.fit(\n",
" X_train_mms,\n",
" y_train\n",
")\n",
"plot_grid_search_results(gs_dt2, 'f1')"
]
},
{
"cell_type": "code",
"execution_count": 30,
"id": "judicial-dealing",
"metadata": {
"execution": {
"iopub.execute_input": "2021-03-21T20:50:53.504679Z",
"iopub.status.busy": "2021-03-21T20:50:53.504490Z",
"iopub.status.idle": "2021-03-21T20:50:53.733725Z",
"shell.execute_reply": "2021-03-21T20:50:53.733131Z",
"shell.execute_reply.started": "2021-03-21T20:50:53.504656Z"
},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"accuracy score: 0.64\n",
"f1 score: 0.37\n",
"recall score: 0.77\n",
"precision score: 0.24\n",
"balanced_accuracy score: 0.69\n",
"roc_auc score: 0.69\n"
]
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {
"image/png": {
"height": 261,
"width": 320
},
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"score_classification_model(gs_dt2, X_test_mms, y_test)"
]
},
{
"cell_type": "code",
"execution_count": 31,
"id": "thrown-monster",
"metadata": {
"execution": {
"iopub.execute_input": "2021-03-21T20:50:53.734952Z",
"iopub.status.busy": "2021-03-21T20:50:53.734803Z",
"iopub.status.idle": "2021-03-21T20:51:37.697629Z",
"shell.execute_reply": "2021-03-21T20:51:37.696512Z",
"shell.execute_reply.started": "2021-03-21T20:50:53.734934Z"
},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Fitting 3 folds for each of 15 candidates, totalling 45 fits\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/usr/local/Caskroom/miniconda/base/envs/t1/lib/python3.9/site-packages/joblib/externals/loky/process_executor.py:688: 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.\n",
" warnings.warn(\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\u001b[1mEstimator:\u001b[0m\n",
"DecisionTreeClassifier(max_depth=128.0, min_samples_split=0.01,\n",
" random_state=2021)\n",
"\n",
"\u001b[1mBest Result (Suggested):\u001b[0m\n",
"\u001b[1m\t train valdn\u001b[0m\n",
"\t f1 0.75 0.74\n",
"\t recall 0.76 0.75\n",
"\t precision 0.74 0.73\n",
"\t balanced_accuracy 0.75 0.74\n",
"\t accuracy 0.75 0.74\n",
"\t roc_auc 0.84 0.83\n",
"\n",
"\u001b[1mParams:\u001b[0m\n",
"\t{'max_depth': 128.0, 'min_samples_split': 0.01}\n",
"\n"
]
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"image/png": {
"height": 459,
"width": 389
},
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# Model 3\n",
"# Using scaled Re-sampled training dataset\n",
"\n",
"params = {\n",
" 'max_depth': np.logspace(1,7,3,base=2),\n",
" 'min_samples_split': np.linspace(.01,.5,5).round(2),\n",
"}\n",
"\n",
"gs_dt3 = GridSearchCV(\n",
" DecisionTreeClassifier(random_state=random_state),\n",
" params, **grid_search_defaults\n",
")\n",
"gs_dt3.fit(\n",
" X_train_resampled_mms,\n",
" y_train_resampled\n",
")\n",
"plot_grid_search_results(gs_dt3, 'f1')"
]
},
{
"cell_type": "code",
"execution_count": 32,
"id": "institutional-skirt",
"metadata": {
"execution": {
"iopub.execute_input": "2021-03-21T20:51:37.699467Z",
"iopub.status.busy": "2021-03-21T20:51:37.699160Z",
"iopub.status.idle": "2021-03-21T20:51:37.921505Z",
"shell.execute_reply": "2021-03-21T20:51:37.920725Z",
"shell.execute_reply.started": "2021-03-21T20:51:37.699439Z"
},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"accuracy score: 0.71\n",
"f1 score: 0.40\n",
"recall score: 0.70\n",
"precision score: 0.28\n",
"balanced_accuracy score: 0.71\n",
"roc_auc score: 0.71\n"
]
},
{
"data": {
"image/png": 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"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {
"image/png": {
"height": 261,
"width": 320
},
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"score_classification_model(gs_dt3, X_test_mms, y_test)"
]
},
{
"cell_type": "markdown",
"id": "burning-mirror",
"metadata": {},
"source": [
"# Plot tree to understand feature importance\n",
"\n",
"If the trees doesn't show up in the notebook, check the html export"
]
},
{
"cell_type": "code",
"execution_count": 33,
"id": "brazilian-contemporary",
"metadata": {
"execution": {
"iopub.execute_input": "2021-03-21T20:51:37.923452Z",
"iopub.status.busy": "2021-03-21T20:51:37.923093Z",
"iopub.status.idle": "2021-03-21T20:51:39.068609Z",
"shell.execute_reply": "2021-03-21T20:51:39.068034Z",
"shell.execute_reply.started": "2021-03-21T20:51:37.923400Z"
},
"tags": []
},
"outputs": [
{
"data": {
"image/svg+xml": [
"<?xml version=\"1.0\" encoding=\"UTF-8\" standalone=\"no\"?>\n",
"<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n",
" \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n",
"<!-- Generated by graphviz version 2.46.1 (0)\n",
" -->\n",
"<!-- Title: Tree Pages: 1 -->\n",
"<svg width=\"1293pt\" height=\"679pt\"\n",
" viewBox=\"0.00 0.00 1292.50 678.50\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n",
"<g id=\"graph0\" class=\"graph\" transform=\"scale(1 1) rotate(0) translate(4 674.5)\">\n",
"<title>Tree</title>\n",
"<polygon fill=\"white\" stroke=\"transparent\" points=\"-4,4 -4,-674.5 1288.5,-674.5 1288.5,4 -4,4\"/>\n",
"<!-- 0 -->\n",
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"<title>0</title>\n",
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"</g>\n",
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"<g id=\"node2\" class=\"node\">\n",
"<title>1</title>\n",
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"</g>\n",
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"<g id=\"edge1\" class=\"edge\">\n",
"<title>0->1</title>\n",
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"</g>\n",
"<!-- 12 -->\n",
"<g id=\"node13\" class=\"node\">\n",
"<title>12</title>\n",
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"<text text-anchor=\"middle\" x=\"1208.5\" y=\"-37.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">samples = 2.8%</text>\n",
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"<text text-anchor=\"middle\" x=\"1208.5\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">class = has_injuries</text>\n",
"</g>\n",
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"<!-- 2 -->\n",
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"<text text-anchor=\"middle\" x=\"868.5\" y=\"-417.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">num_units <= 0.136</text>\n",
"<text text-anchor=\"middle\" x=\"868.5\" y=\"-402.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">gini = 0.193</text>\n",
"<text text-anchor=\"middle\" x=\"868.5\" y=\"-387.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">samples = 95.6%</text>\n",
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"<text text-anchor=\"middle\" x=\"868.5\" y=\"-357.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">class = no_injuries</text>\n",
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"<!-- 11 -->\n",
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"<title>11</title>\n",
"<path fill=\"#8fc8f0\" stroke=\"black\" d=\"M1102.5,-68C1102.5,-68 974.5,-68 974.5,-68 968.5,-68 962.5,-62 962.5,-56 962.5,-56 962.5,-12 962.5,-12 962.5,-6 968.5,0 974.5,0 974.5,0 1102.5,0 1102.5,0 1108.5,0 1114.5,-6 1114.5,-12 1114.5,-12 1114.5,-56 1114.5,-56 1114.5,-62 1108.5,-68 1102.5,-68\"/>\n",
"<text text-anchor=\"middle\" x=\"1038.5\" y=\"-52.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">gini = 0.422</text>\n",
"<text text-anchor=\"middle\" x=\"1038.5\" y=\"-37.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">samples = 1.6%</text>\n",
"<text text-anchor=\"middle\" x=\"1038.5\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">value = [0.303, 0.697]</text>\n",
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"</g>\n",
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"<g id=\"edge11\" class=\"edge\">\n",
"<title>1->11</title>\n",
"<path fill=\"none\" stroke=\"black\" d=\"M1038.5,-468.18C1038.5,-379.4 1038.5,-169.45 1038.5,-78.39\"/>\n",
"<polygon fill=\"black\" stroke=\"black\" points=\"1042,-78.14 1038.5,-68.14 1035,-78.14 1042,-78.14\"/>\n",
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"<!-- 3 -->\n",
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"<title>3</title>\n",
"<path fill=\"#e88e4e\" stroke=\"black\" d=\"M773.5,-313.5C773.5,-313.5 453.5,-313.5 453.5,-313.5 447.5,-313.5 441.5,-307.5 441.5,-301.5 441.5,-301.5 441.5,-242.5 441.5,-242.5 441.5,-236.5 447.5,-230.5 453.5,-230.5 453.5,-230.5 773.5,-230.5 773.5,-230.5 779.5,-230.5 785.5,-236.5 785.5,-242.5 785.5,-242.5 785.5,-301.5 785.5,-301.5 785.5,-307.5 779.5,-313.5 773.5,-313.5\"/>\n",
"<text text-anchor=\"middle\" x=\"613.5\" y=\"-298.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">first_crash_type_PARKED MOTOR VEHICLE <= 0.5</text>\n",
"<text text-anchor=\"middle\" x=\"613.5\" y=\"-283.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">gini = 0.174</text>\n",
"<text text-anchor=\"middle\" x=\"613.5\" y=\"-268.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">samples = 88.9%</text>\n",
"<text text-anchor=\"middle\" x=\"613.5\" y=\"-253.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">value = [0.903, 0.097]</text>\n",
"<text text-anchor=\"middle\" x=\"613.5\" y=\"-238.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">class = no_injuries</text>\n",
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"<title>2->3</title>\n",
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"<polygon fill=\"black\" stroke=\"black\" points=\"712.37,-314.51 701.82,-313.52 709.45,-320.87 712.37,-314.51\"/>\n",
"</g>\n",
"<!-- 10 -->\n",
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"<title>10</title>\n",
"<path fill=\"#eeaf81\" stroke=\"black\" d=\"M932.5,-68C932.5,-68 804.5,-68 804.5,-68 798.5,-68 792.5,-62 792.5,-56 792.5,-56 792.5,-12 792.5,-12 792.5,-6 798.5,0 804.5,0 804.5,0 932.5,0 932.5,0 938.5,0 944.5,-6 944.5,-12 944.5,-12 944.5,-56 944.5,-56 944.5,-62 938.5,-68 932.5,-68\"/>\n",
"<text text-anchor=\"middle\" x=\"868.5\" y=\"-52.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">gini = 0.391</text>\n",
"<text text-anchor=\"middle\" x=\"868.5\" y=\"-37.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">samples = 6.7%</text>\n",
"<text text-anchor=\"middle\" x=\"868.5\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">value = [0.734, 0.266]</text>\n",
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"</g>\n",
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"<g id=\"edge10\" class=\"edge\">\n",
"<title>2->10</title>\n",
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"<polygon fill=\"black\" stroke=\"black\" points=\"872,-78.18 868.5,-68.18 865,-78.18 872,-78.18\"/>\n",
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"<text text-anchor=\"middle\" x=\"184.5\" y=\"-149.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">samples = 68.8%</text>\n",
"<text text-anchor=\"middle\" x=\"184.5\" y=\"-134.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">value = [0.881, 0.119]</text>\n",
"<text text-anchor=\"middle\" x=\"184.5\" y=\"-119.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">class = no_injuries</text>\n",
"</g>\n",
"<!-- 3->4 -->\n",
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"<text text-anchor=\"middle\" x=\"613.5\" y=\"-179.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">prim_contributory_cause_PHYSICAL CONDITION OF DRIVER <= 0.5</text>\n",
"<text text-anchor=\"middle\" x=\"613.5\" y=\"-164.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">gini = 0.037</text>\n",
"<text text-anchor=\"middle\" x=\"613.5\" y=\"-149.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">samples = 20.2%</text>\n",
"<text text-anchor=\"middle\" x=\"613.5\" y=\"-134.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">value = [0.981, 0.019]</text>\n",
"<text text-anchor=\"middle\" x=\"613.5\" y=\"-119.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">class = no_injuries</text>\n",
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"<title>9</title>\n",
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"<text text-anchor=\"middle\" x=\"656.5\" y=\"-52.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">gini = 0.396</text>\n",
"<text text-anchor=\"middle\" x=\"656.5\" y=\"-37.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">samples = 0.2%</text>\n",
"<text text-anchor=\"middle\" x=\"656.5\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">value = [0.728, 0.272]</text>\n",
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"text/plain": [
"<graphviz.files.Source at 0x1b4a0c9a0>"
]
},
"execution_count": 33,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Original Training Dataset (Not-Oversampled)\n",
"\n",
"params = {\n",
" 'max_depth': 5,\n",
" 'min_samples_split': .1,\n",
"# 'class_weight': 'balanced',\n",
"}\n",
"clf = DecisionTreeClassifier(**params)\n",
"clf.fit(X_train_mms, y_train)\n",
"\n",
"fn = X_train.columns.values\n",
"cn = ['no_injuries','has_injuries']\n",
"\n",
"_ = export_graphviz(clf,rounded=True,leaves_parallel=True,\n",
" out_file=None,\n",
" feature_names = X_train.columns.values, \n",
" class_names= cn,\n",
" filled = True,\n",
" proportion= True\n",
" )\n",
"\n",
"graphviz.Source(_)"
]
},
{
"cell_type": "code",
"execution_count": 34,
"id": "effective-foster",
"metadata": {
"execution": {
"iopub.execute_input": "2021-03-21T20:51:39.070052Z",
"iopub.status.busy": "2021-03-21T20:51:39.069865Z",
"iopub.status.idle": "2021-03-21T20:51:40.287578Z",
"shell.execute_reply": "2021-03-21T20:51:40.287057Z",
"shell.execute_reply.started": "2021-03-21T20:51:39.070030Z"
},
"tags": []
},
"outputs": [
{
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"<text text-anchor=\"middle\" x=\"1700\" y=\"-640.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">gini = 0.5</text>\n",
"<text text-anchor=\"middle\" x=\"1700\" y=\"-625.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">samples = 100.0%</text>\n",
"<text text-anchor=\"middle\" x=\"1700\" y=\"-610.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">value = [0.5, 0.5]</text>\n",
"<text text-anchor=\"middle\" x=\"1700\" y=\"-595.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">class = no_injuries</text>\n",
"</g>\n",
"<!-- 1 -->\n",
"<g id=\"node2\" class=\"node\">\n",
"<title>1</title>\n",
"<path fill=\"#fbeadd\" stroke=\"black\" d=\"M1648,-551.5C1648,-551.5 1328,-551.5 1328,-551.5 1322,-551.5 1316,-545.5 1316,-539.5 1316,-539.5 1316,-480.5 1316,-480.5 1316,-474.5 1322,-468.5 1328,-468.5 1328,-468.5 1648,-468.5 1648,-468.5 1654,-468.5 1660,-474.5 1660,-480.5 1660,-480.5 1660,-539.5 1660,-539.5 1660,-545.5 1654,-551.5 1648,-551.5\"/>\n",
"<text text-anchor=\"middle\" x=\"1488\" y=\"-536.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">first_crash_type_PARKED MOTOR VEHICLE <= 0.5</text>\n",
"<text text-anchor=\"middle\" x=\"1488\" y=\"-521.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">gini = 0.496</text>\n",
"<text text-anchor=\"middle\" x=\"1488\" y=\"-506.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">samples = 91.1%</text>\n",
"<text text-anchor=\"middle\" x=\"1488\" y=\"-491.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">value = [0.547, 0.453]</text>\n",
"<text text-anchor=\"middle\" x=\"1488\" y=\"-476.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">class = no_injuries</text>\n",
"</g>\n",
"<!-- 0->1 -->\n",
"<g id=\"edge1\" class=\"edge\">\n",
"<title>0->1</title>\n",
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"<polygon fill=\"black\" stroke=\"black\" points=\"1571.87,-553.29 1561.42,-551.52 1568.49,-559.42 1571.87,-553.29\"/>\n",
"<text text-anchor=\"middle\" x=\"1568.36\" y=\"-571.84\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">True</text>\n",
"</g>\n",
"<!-- 20 -->\n",
"<g id=\"node21\" class=\"node\">\n",
"<title>20</title>\n",
"<path fill=\"#3d9fe6\" stroke=\"black\" d=\"M1871,-68C1871,-68 1743,-68 1743,-68 1737,-68 1731,-62 1731,-56 1731,-56 1731,-12 1731,-12 1731,-6 1737,0 1743,0 1743,0 1871,0 1871,0 1877,0 1883,-6 1883,-12 1883,-12 1883,-56 1883,-56 1883,-62 1877,-68 1871,-68\"/>\n",
"<text text-anchor=\"middle\" x=\"1807\" y=\"-52.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">gini = 0.042</text>\n",
"<text text-anchor=\"middle\" x=\"1807\" y=\"-37.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">samples = 8.9%</text>\n",
"<text text-anchor=\"middle\" x=\"1807\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">value = [0.022, 0.978]</text>\n",
"<text text-anchor=\"middle\" x=\"1807\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">class = has_injuries</text>\n",
"</g>\n",
"<!-- 0->20 -->\n",
"<g id=\"edge20\" class=\"edge\">\n",
"<title>0->20</title>\n",
"<path fill=\"none\" stroke=\"black\" d=\"M1718.39,-587.43C1748.99,-519.95 1807,-392 1807,-392 1807,-392 1807,-392 1807,-271 1807,-271 1807,-146.16 1807,-78.08\"/>\n",
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"<text text-anchor=\"middle\" x=\"1824.68\" y=\"-82.04\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">False</text>\n",
"</g>\n",
"<!-- 2 -->\n",
"<g id=\"node3\" class=\"node\">\n",
"<title>2</title>\n",
"<path fill=\"#f7fbfe\" stroke=\"black\" d=\"M977.5,-432.5C977.5,-432.5 632.5,-432.5 632.5,-432.5 626.5,-432.5 620.5,-426.5 620.5,-420.5 620.5,-420.5 620.5,-361.5 620.5,-361.5 620.5,-355.5 626.5,-349.5 632.5,-349.5 632.5,-349.5 977.5,-349.5 977.5,-349.5 983.5,-349.5 989.5,-355.5 989.5,-361.5 989.5,-361.5 989.5,-420.5 989.5,-420.5 989.5,-426.5 983.5,-432.5 977.5,-432.5\"/>\n",
"<text text-anchor=\"middle\" x=\"805\" y=\"-417.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">first_crash_type_SIDESWIPE SAME DIRECTION <= 0.5</text>\n",
"<text text-anchor=\"middle\" x=\"805\" y=\"-402.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">gini = 0.5</text>\n",
"<text text-anchor=\"middle\" x=\"805\" y=\"-387.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">samples = 76.0%</text>\n",
"<text text-anchor=\"middle\" x=\"805\" y=\"-372.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">value = [0.49, 0.51]</text>\n",
"<text text-anchor=\"middle\" x=\"805\" y=\"-357.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">class = has_injuries</text>\n",
"</g>\n",
"<!-- 1->2 -->\n",
"<g id=\"edge2\" class=\"edge\">\n",
"<title>1->2</title>\n",
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"<polygon fill=\"black\" stroke=\"black\" points=\"1000.02,-421.86 989.57,-423.62 998.83,-428.76 1000.02,-421.86\"/>\n",
"</g>\n",
"<!-- 13 -->\n",
"<g id=\"node14\" class=\"node\">\n",
"<title>13</title>\n",
"<path fill=\"#ea9a61\" stroke=\"black\" d=\"M1552,-432.5C1552,-432.5 1424,-432.5 1424,-432.5 1418,-432.5 1412,-426.5 1412,-420.5 1412,-420.5 1412,-361.5 1412,-361.5 1412,-355.5 1418,-349.5 1424,-349.5 1424,-349.5 1552,-349.5 1552,-349.5 1558,-349.5 1564,-355.5 1564,-361.5 1564,-361.5 1564,-420.5 1564,-420.5 1564,-426.5 1558,-432.5 1552,-432.5\"/>\n",
"<text text-anchor=\"middle\" x=\"1488\" y=\"-417.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">num_units <= 0.136</text>\n",
"<text text-anchor=\"middle\" x=\"1488\" y=\"-402.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">gini = 0.28</text>\n",
"<text text-anchor=\"middle\" x=\"1488\" y=\"-387.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">samples = 15.1%</text>\n",
"<text text-anchor=\"middle\" x=\"1488\" y=\"-372.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">value = [0.832, 0.168]</text>\n",
"<text text-anchor=\"middle\" x=\"1488\" y=\"-357.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">class = no_injuries</text>\n",
"</g>\n",
"<!-- 1->13 -->\n",
"<g id=\"edge13\" class=\"edge\">\n",
"<title>1->13</title>\n",
"<path fill=\"none\" stroke=\"black\" d=\"M1488,-468.41C1488,-460.15 1488,-451.36 1488,-442.8\"/>\n",
"<polygon fill=\"black\" stroke=\"black\" points=\"1491.5,-442.52 1488,-432.52 1484.5,-442.52 1491.5,-442.52\"/>\n",
"</g>\n",
"<!-- 3 -->\n",
"<g id=\"node4\" class=\"node\">\n",
"<title>3</title>\n",
"<path fill=\"#d6ebfa\" stroke=\"black\" d=\"M540,-313.5C540,-313.5 292,-313.5 292,-313.5 286,-313.5 280,-307.5 280,-301.5 280,-301.5 280,-242.5 280,-242.5 280,-236.5 286,-230.5 292,-230.5 292,-230.5 540,-230.5 540,-230.5 546,-230.5 552,-236.5 552,-242.5 552,-242.5 552,-301.5 552,-301.5 552,-307.5 546,-313.5 540,-313.5\"/>\n",
"<text text-anchor=\"middle\" x=\"416\" y=\"-298.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">first_crash_type_PEDALCYCLIST <= 0.5</text>\n",
"<text text-anchor=\"middle\" x=\"416\" y=\"-283.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">gini = 0.493</text>\n",
"<text text-anchor=\"middle\" x=\"416\" y=\"-268.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">samples = 64.6%</text>\n",
"<text text-anchor=\"middle\" x=\"416\" y=\"-253.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">value = [0.443, 0.557]</text>\n",
"<text text-anchor=\"middle\" x=\"416\" y=\"-238.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">class = has_injuries</text>\n",
"</g>\n",
"<!-- 2->3 -->\n",
"<g id=\"edge3\" class=\"edge\">\n",
"<title>2->3</title>\n",
"<path fill=\"none\" stroke=\"black\" d=\"M670.31,-349.49C634.84,-338.82 596.44,-327.27 560.48,-316.46\"/>\n",
"<polygon fill=\"black\" stroke=\"black\" points=\"561.49,-313.1 550.9,-313.57 559.47,-319.81 561.49,-313.1\"/>\n",
"</g>\n",
"<!-- 8 -->\n",
"<g id=\"node9\" class=\"node\">\n",
"<title>8</title>\n",
"<path fill=\"#edaa79\" stroke=\"black\" d=\"M869,-313.5C869,-313.5 741,-313.5 741,-313.5 735,-313.5 729,-307.5 729,-301.5 729,-301.5 729,-242.5 729,-242.5 729,-236.5 735,-230.5 741,-230.5 741,-230.5 869,-230.5 869,-230.5 875,-230.5 881,-236.5 881,-242.5 881,-242.5 881,-301.5 881,-301.5 881,-307.5 875,-313.5 869,-313.5\"/>\n",
"<text text-anchor=\"middle\" x=\"805\" y=\"-298.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">num_units <= 0.136</text>\n",
"<text text-anchor=\"middle\" x=\"805\" y=\"-283.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">gini = 0.369</text>\n",
"<text text-anchor=\"middle\" x=\"805\" y=\"-268.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">samples = 11.3%</text>\n",
"<text text-anchor=\"middle\" x=\"805\" y=\"-253.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">value = [0.756, 0.244]</text>\n",
"<text text-anchor=\"middle\" x=\"805\" y=\"-238.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">class = no_injuries</text>\n",
"</g>\n",
"<!-- 2->8 -->\n",
"<g id=\"edge8\" class=\"edge\">\n",
"<title>2->8</title>\n",
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"<polygon fill=\"black\" stroke=\"black\" points=\"808.5,-323.52 805,-313.52 801.5,-323.52 808.5,-323.52\"/>\n",
"</g>\n",
"<!-- 4 -->\n",
"<g id=\"node5\" class=\"node\">\n",
"<title>4</title>\n",
"<path fill=\"#e9f4fc\" stroke=\"black\" d=\"M304,-194.5C304,-194.5 188,-194.5 188,-194.5 182,-194.5 176,-188.5 176,-182.5 176,-182.5 176,-123.5 176,-123.5 176,-117.5 182,-111.5 188,-111.5 188,-111.5 304,-111.5 304,-111.5 310,-111.5 316,-117.5 316,-123.5 316,-123.5 316,-182.5 316,-182.5 316,-188.5 310,-194.5 304,-194.5\"/>\n",
"<text text-anchor=\"middle\" x=\"246\" y=\"-179.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">num_units <= 0.136</text>\n",
"<text text-anchor=\"middle\" x=\"246\" y=\"-164.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">gini = 0.498</text>\n",
"<text text-anchor=\"middle\" x=\"246\" y=\"-149.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">samples = 60.3%</text>\n",
"<text text-anchor=\"middle\" x=\"246\" y=\"-134.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">value = [0.47, 0.53]</text>\n",
"<text text-anchor=\"middle\" x=\"246\" y=\"-119.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">class = has_injuries</text>\n",
"</g>\n",
"<!-- 3->4 -->\n",
"<g id=\"edge4\" class=\"edge\">\n",
"<title>3->4</title>\n",
"<path fill=\"none\" stroke=\"black\" d=\"M357.02,-230.41C342.91,-220.7 327.74,-210.26 313.29,-200.31\"/>\n",
"<polygon fill=\"black\" stroke=\"black\" points=\"315.1,-197.31 304.88,-194.52 311.13,-203.07 315.1,-197.31\"/>\n",
"</g>\n",
"<!-- 7 -->\n",
"<g id=\"node8\" class=\"node\">\n",
"<title>7</title>\n",
"<path fill=\"#47a4e7\" stroke=\"black\" d=\"M480,-68C480,-68 352,-68 352,-68 346,-68 340,-62 340,-56 340,-56 340,-12 340,-12 340,-6 346,0 352,0 352,0 480,0 480,0 486,0 492,-6 492,-12 492,-12 492,-56 492,-56 492,-62 486,-68 480,-68\"/>\n",
"<text text-anchor=\"middle\" x=\"416\" y=\"-52.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">gini = 0.122</text>\n",
"<text text-anchor=\"middle\" x=\"416\" y=\"-37.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">samples = 4.3%</text>\n",
"<text text-anchor=\"middle\" x=\"416\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">value = [0.065, 0.935]</text>\n",
"<text text-anchor=\"middle\" x=\"416\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">class = has_injuries</text>\n",
"</g>\n",
"<!-- 3->7 -->\n",
"<g id=\"edge7\" class=\"edge\">\n",
"<title>3->7</title>\n",
"<path fill=\"none\" stroke=\"black\" d=\"M416,-230.43C416,-188.06 416,-121.85 416,-78.44\"/>\n",
"<polygon fill=\"black\" stroke=\"black\" points=\"419.5,-78.19 416,-68.19 412.5,-78.19 419.5,-78.19\"/>\n",
"</g>\n",
"<!-- 5 -->\n",
"<g id=\"node6\" class=\"node\">\n",
"<title>5</title>\n",
"<path fill=\"#fcfeff\" stroke=\"black\" d=\"M140,-68C140,-68 12,-68 12,-68 6,-68 0,-62 0,-56 0,-56 0,-12 0,-12 0,-6 6,0 12,0 12,0 140,0 140,0 146,0 152,-6 152,-12 152,-12 152,-56 152,-56 152,-62 146,-68 140,-68\"/>\n",
"<text text-anchor=\"middle\" x=\"76\" y=\"-52.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">gini = 0.5</text>\n",
"<text text-anchor=\"middle\" x=\"76\" y=\"-37.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">samples = 54.1%</text>\n",
"<text text-anchor=\"middle\" x=\"76\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">value = [0.497, 0.503]</text>\n",
"<text text-anchor=\"middle\" x=\"76\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">class = has_injuries</text>\n",
"</g>\n",
"<!-- 4->5 -->\n",
"<g id=\"edge5\" class=\"edge\">\n",
"<title>4->5</title>\n",
"<path fill=\"none\" stroke=\"black\" d=\"M187.02,-111.41C169.38,-99.27 150.09,-85.99 132.61,-73.96\"/>\n",
"<polygon fill=\"black\" stroke=\"black\" points=\"134.41,-70.95 124.19,-68.17 130.44,-76.72 134.41,-70.95\"/>\n",
"</g>\n",
"<!-- 6 -->\n",
"<g id=\"node7\" class=\"node\">\n",
"<title>6</title>\n",
"<path fill=\"#77bced\" stroke=\"black\" d=\"M310,-68C310,-68 182,-68 182,-68 176,-68 170,-62 170,-56 170,-56 170,-12 170,-12 170,-6 176,0 182,0 182,0 310,0 310,0 316,0 322,-6 322,-12 322,-12 322,-56 322,-56 322,-62 316,-68 310,-68\"/>\n",
"<text text-anchor=\"middle\" x=\"246\" y=\"-52.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">gini = 0.364</text>\n",
"<text text-anchor=\"middle\" x=\"246\" y=\"-37.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">samples = 6.3%</text>\n",
"<text text-anchor=\"middle\" x=\"246\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">value = [0.239, 0.761]</text>\n",
"<text text-anchor=\"middle\" x=\"246\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">class = has_injuries</text>\n",
"</g>\n",
"<!-- 4->6 -->\n",
"<g id=\"edge6\" class=\"edge\">\n",
"<title>4->6</title>\n",
"<path fill=\"none\" stroke=\"black\" d=\"M246,-111.41C246,-100.7 246,-89.12 246,-78.28\"/>\n",
"<polygon fill=\"black\" stroke=\"black\" points=\"249.5,-78.17 246,-68.17 242.5,-78.17 249.5,-78.17\"/>\n",
"</g>\n",
"<!-- 9 -->\n",
"<g id=\"node10\" class=\"node\">\n",
"<title>9</title>\n",
"<path fill=\"#eca470\" stroke=\"black\" d=\"M800,-194.5C800,-194.5 672,-194.5 672,-194.5 666,-194.5 660,-188.5 660,-182.5 660,-182.5 660,-123.5 660,-123.5 660,-117.5 666,-111.5 672,-111.5 672,-111.5 800,-111.5 800,-111.5 806,-111.5 812,-117.5 812,-123.5 812,-123.5 812,-182.5 812,-182.5 812,-188.5 806,-194.5 800,-194.5\"/>\n",
"<text text-anchor=\"middle\" x=\"736\" y=\"-179.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">longitude <= 0.781</text>\n",
"<text text-anchor=\"middle\" x=\"736\" y=\"-164.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">gini = 0.341</text>\n",
"<text text-anchor=\"middle\" x=\"736\" y=\"-149.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">samples = 10.6%</text>\n",
"<text text-anchor=\"middle\" x=\"736\" y=\"-134.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">value = [0.782, 0.218]</text>\n",
"<text text-anchor=\"middle\" x=\"736\" y=\"-119.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">class = no_injuries</text>\n",
"</g>\n",
"<!-- 8->9 -->\n",
"<g id=\"edge9\" class=\"edge\">\n",
"<title>8->9</title>\n",
"<path fill=\"none\" stroke=\"black\" d=\"M781.06,-230.41C775.92,-221.7 770.44,-212.4 765.13,-203.39\"/>\n",
"<polygon fill=\"black\" stroke=\"black\" points=\"767.99,-201.36 759.9,-194.52 761.96,-204.91 767.99,-201.36\"/>\n",
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"<!-- 12 -->\n",
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"<title>12</title>\n",
"<path fill=\"#acd6f4\" stroke=\"black\" d=\"M970,-68C970,-68 842,-68 842,-68 836,-68 830,-62 830,-56 830,-56 830,-12 830,-12 830,-6 836,0 842,0 842,0 970,0 970,0 976,0 982,-6 982,-12 982,-12 982,-56 982,-56 982,-62 976,-68 970,-68\"/>\n",
"<text text-anchor=\"middle\" x=\"906\" y=\"-52.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">gini = 0.464</text>\n",
"<text text-anchor=\"middle\" x=\"906\" y=\"-37.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">samples = 0.7%</text>\n",
"<text text-anchor=\"middle\" x=\"906\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">value = [0.367, 0.633]</text>\n",
"<text text-anchor=\"middle\" x=\"906\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">class = has_injuries</text>\n",
"</g>\n",
"<!-- 8->12 -->\n",
"<g id=\"edge12\" class=\"edge\">\n",
"<title>8->12</title>\n",
"<path fill=\"none\" stroke=\"black\" d=\"M822.36,-230.43C840.61,-187.79 869.19,-121.01 887.76,-77.61\"/>\n",
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"<!-- 10 -->\n",
"<g id=\"node11\" class=\"node\">\n",
"<title>10</title>\n",
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"_ = export_graphviz(clf,rounded=True,leaves_parallel=True,\n",
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{
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