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+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## 1. Business Understanding¶\n",
+ "This case study is intended to assist technology companies in developing and improving components for autonomous vehicles.\n",
+ "In doing so, this case study poses the question:\n",
+ "In which areas are the weaknesses of the tested systems and how can these be classified?\n",
+ "The question will be answered by classifying the reasons for the human test driver's intervention in the system. In doing so, the reasons are to be classified into different categories:\n",
+ "- Software problems\n",
+ "- hardware problems\n",
+ "- Software and hardware problems (problems that occur in combination)\n",
+ "- Problems caused by objects of traffic control (e.g. malfunctions of traffic light systems)\n",
+ "- problems caused by other road users\n",
+ "- external influences (including e.g. blockages, hidden elements, weather and road conditions)\n",
+ "- other problems"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## 2. Data and Data Understanding \n",
+ "The underlying dataset was obtained from Kaggle and shows necessary interventions by a driver in autonomous driving vehicle technology.\n",
+ "It was recorded from December 1, 2018 to November 30, 2019 and is licensed under U.S. Government Works.\n",
+ "The data processing is done with the help of a Jupyter notebook, which is included in the most popular data science platform \"Anaconda\".\n",
+ "The data set is in 8885 x 9 format.\n",
+ "The following data was recorded:\n",
+ "- Manufacturer\n",
+ "- Approval number\n",
+ "- date\n",
+ "- Vehicle identification number\n",
+ "- Possibility of operation without driver\n",
+ "- Is there a driver on site?\n",
+ "- Autonomous driving interrupted by AV system, test driver, remote control, or passenger\n",
+ "- Location of incident: interstate, highway, expressway, rural road, street or parking lot\n",
+ "- Description of causes"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## 2.1. Import of Relevant Modules"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 76,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import numpy as np\n",
+ "import pandas as pd\n",
+ "import statsmodels.api as sm\n",
+ "import matplotlib.pyplot as plt\n",
+ "import seaborn as sns\n",
+ "sns.set()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 77,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "'2.0.3'"
+ ]
+ },
+ "execution_count": 77,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "pd.__version__"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## 2.2 Read Data"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 78,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "raw_data = pd.read_csv('https://storage.googleapis.com/ml-service-repository-datastorage/Improvement_of_components_for_autonomous_motor_vehicles_data.csv')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 79,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "<div>\n",
+ "<style scoped>\n",
+ " .dataframe tbody tr th:only-of-type {\n",
+ " vertical-align: middle;\n",
+ " }\n",
+ "\n",
+ " .dataframe tbody tr th {\n",
+ " vertical-align: top;\n",
+ " }\n",
+ "\n",
+ " .dataframe thead th {\n",
+ " text-align: right;\n",
+ " }\n",
+ "</style>\n",
+ "<table border=\"1\" class=\"dataframe\">\n",
+ " <thead>\n",
+ " <tr style=\"text-align: right;\">\n",
+ " <th></th>\n",
+ " <th>Manufacturer</th>\n",
+ " <th>Permit Number</th>\n",
+ " <th>DATE</th>\n",
+ " <th>VIN NUMBER</th>\n",
+ " <th>VEHICLE IS CAPABLE OF OPERATING WITHOUT A DRIVER\\n(Yes or No)</th>\n",
+ " <th>DRIVER PRESENT\\n(Yes or No)</th>\n",
+ " <th>DISENGAGEMENT INITIATED BY\\n(AV System, Test Driver, Remote Operator, or Passenger)</th>\n",
+ " <th>DISENGAGEMENT\\nLOCATION\\n(Interstate, Freeway, Highway, Rural Road, Street, or Parking Facility)</th>\n",
+ " <th>DESCRIPTION OF FACTS CAUSING DISENGAGEMENT</th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " <tr>\n",
+ " <th>0</th>\n",
+ " <td>AImotive Inc.</td>\n",
+ " <td>AVT003</td>\n",
+ " <td>12.06.2018</td>\n",
+ " <td>JTDKN3DU5A1092792</td>\n",
+ " <td>No</td>\n",
+ " <td>Yes</td>\n",
+ " <td>Test Driver</td>\n",
+ " <td>Freeway</td>\n",
+ " <td>Lane change maneuver: risk of lane departure, ...</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>1</th>\n",
+ " <td>AImotive Inc.</td>\n",
+ " <td>AVT003</td>\n",
+ " <td>12.10.2018</td>\n",
+ " <td>JTDKN3DU5A1092792</td>\n",
+ " <td>No</td>\n",
+ " <td>Yes</td>\n",
+ " <td>Test Driver</td>\n",
+ " <td>Freeway</td>\n",
+ " <td>Lane change maneuver: risk of lane departure, ...</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>2</th>\n",
+ " <td>AImotive Inc.</td>\n",
+ " <td>AVT003</td>\n",
+ " <td>12.10.2018</td>\n",
+ " <td>JTDKN3DU5A1092792</td>\n",
+ " <td>No</td>\n",
+ " <td>Yes</td>\n",
+ " <td>Test Driver</td>\n",
+ " <td>Freeway</td>\n",
+ " <td>Lane change maneuver: risk of lane departure, ...</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>3</th>\n",
+ " <td>AImotive Inc.</td>\n",
+ " <td>AVT003</td>\n",
+ " <td>04.23.2019</td>\n",
+ " <td>JTDKN3DU5A1092792</td>\n",
+ " <td>No</td>\n",
+ " <td>Yes</td>\n",
+ " <td>Test Driver</td>\n",
+ " <td>Freeway</td>\n",
+ " <td>Lane change maneuver: risk of lane departure, ...</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>4</th>\n",
+ " <td>AImotive Inc.</td>\n",
+ " <td>AVT003</td>\n",
+ " <td>05.14.2019</td>\n",
+ " <td>JTDKN3DU5A1092792</td>\n",
+ " <td>No</td>\n",
+ " <td>Yes</td>\n",
+ " <td>Test Driver</td>\n",
+ " <td>Freeway</td>\n",
+ " <td>Lane change maneuver to the exit lane: risk of...</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "</div>"
+ ],
+ "text/plain": [
+ " Manufacturer Permit Number DATE VIN NUMBER \\\n",
+ "0 AImotive Inc. AVT003 12.06.2018 JTDKN3DU5A1092792 \n",
+ "1 AImotive Inc. AVT003 12.10.2018 JTDKN3DU5A1092792 \n",
+ "2 AImotive Inc. AVT003 12.10.2018 JTDKN3DU5A1092792 \n",
+ "3 AImotive Inc. AVT003 04.23.2019 JTDKN3DU5A1092792 \n",
+ "4 AImotive Inc. AVT003 05.14.2019 JTDKN3DU5A1092792 \n",
+ "\n",
+ " VEHICLE IS CAPABLE OF OPERATING WITHOUT A DRIVER\\n(Yes or No) \\\n",
+ "0 No \n",
+ "1 No \n",
+ "2 No \n",
+ "3 No \n",
+ "4 No \n",
+ "\n",
+ " DRIVER PRESENT\\n(Yes or No) \\\n",
+ "0 Yes \n",
+ "1 Yes \n",
+ "2 Yes \n",
+ "3 Yes \n",
+ "4 Yes \n",
+ "\n",
+ " DISENGAGEMENT INITIATED BY\\n(AV System, Test Driver, Remote Operator, or Passenger) \\\n",
+ "0 Test Driver \n",
+ "1 Test Driver \n",
+ "2 Test Driver \n",
+ "3 Test Driver \n",
+ "4 Test Driver \n",
+ "\n",
+ " DISENGAGEMENT\\nLOCATION\\n(Interstate, Freeway, Highway, Rural Road, Street, or Parking Facility) \\\n",
+ "0 Freeway \n",
+ "1 Freeway \n",
+ "2 Freeway \n",
+ "3 Freeway \n",
+ "4 Freeway \n",
+ "\n",
+ " DESCRIPTION OF FACTS CAUSING DISENGAGEMENT \n",
+ "0 Lane change maneuver: risk of lane departure, ... \n",
+ "1 Lane change maneuver: risk of lane departure, ... \n",
+ "2 Lane change maneuver: risk of lane departure, ... \n",
+ "3 Lane change maneuver: risk of lane departure, ... \n",
+ "4 Lane change maneuver to the exit lane: risk of... "
+ ]
+ },
+ "execution_count": 79,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "raw_data.to_csv('rawdata.csv', index=False)\n",
+ "raw_data.head()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## 2.3. Data Cleaning"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 80,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "<class 'pandas.core.frame.DataFrame'>\n",
+ "RangeIndex: 8885 entries, 0 to 8884\n",
+ "Data columns (total 9 columns):\n",
+ " # Column Non-Null Count Dtype \n",
+ "--- ------ -------------- ----- \n",
+ " 0 Manufacturer 8885 non-null object\n",
+ " 1 Permit Number 8885 non-null object\n",
+ " 2 DATE 8884 non-null object\n",
+ " 3 VIN NUMBER 8884 non-null object\n",
+ " 4 VEHICLE IS CAPABLE OF OPERATING WITHOUT A DRIVER\n",
+ "(Yes or No) 8884 non-null object\n",
+ " 5 DRIVER PRESENT\n",
+ "(Yes or No) 8884 non-null object\n",
+ " 6 DISENGAGEMENT INITIATED BY\n",
+ "(AV System, Test Driver, Remote Operator, or Passenger) 8884 non-null object\n",
+ " 7 DISENGAGEMENT\n",
+ "LOCATION\n",
+ "(Interstate, Freeway, Highway, Rural Road, Street, or Parking Facility) 8884 non-null object\n",
+ " 8 DESCRIPTION OF FACTS CAUSING DISENGAGEMENT 8884 non-null object\n",
+ "dtypes: object(9)\n",
+ "memory usage: 624.9+ KB\n"
+ ]
+ }
+ ],
+ "source": [
+ "raw_data.info()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 81,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "<div>\n",
+ "<style scoped>\n",
+ " .dataframe tbody tr th:only-of-type {\n",
+ " vertical-align: middle;\n",
+ " }\n",
+ "\n",
+ " .dataframe tbody tr th {\n",
+ " vertical-align: top;\n",
+ " }\n",
+ "\n",
+ " .dataframe thead th {\n",
+ " text-align: right;\n",
+ " }\n",
+ "</style>\n",
+ "<table border=\"1\" class=\"dataframe\">\n",
+ " <thead>\n",
+ " <tr style=\"text-align: right;\">\n",
+ " <th></th>\n",
+ " <th>Manufacturer</th>\n",
+ " <th>Permit Number</th>\n",
+ " <th>DATE</th>\n",
+ " <th>VIN NUMBER</th>\n",
+ " <th>VEHICLE IS CAPABLE OF OPERATING WITHOUT A DRIVER\\n(Yes or No)</th>\n",
+ " <th>DRIVER PRESENT\\n(Yes or No)</th>\n",
+ " <th>DISENGAGEMENT INITIATED BY\\n(AV System, Test Driver, Remote Operator, or Passenger)</th>\n",
+ " <th>DISENGAGEMENT\\nLOCATION\\n(Interstate, Freeway, Highway, Rural Road, Street, or Parking Facility)</th>\n",
+ " <th>DESCRIPTION OF FACTS CAUSING DISENGAGEMENT</th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " <tr>\n",
+ " <th>count</th>\n",
+ " <td>8885</td>\n",
+ " <td>8885</td>\n",
+ " <td>8884</td>\n",
+ " <td>8884</td>\n",
+ " <td>8884</td>\n",
+ " <td>8884</td>\n",
+ " <td>8884</td>\n",
+ " <td>8884</td>\n",
+ " <td>8884</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>unique</th>\n",
+ " <td>28</td>\n",
+ " <td>27</td>\n",
+ " <td>3711</td>\n",
+ " <td>289</td>\n",
+ " <td>5</td>\n",
+ " <td>4</td>\n",
+ " <td>4</td>\n",
+ " <td>11</td>\n",
+ " <td>469</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>top</th>\n",
+ " <td>Toyota Research Institute</td>\n",
+ " <td>AVT050</td>\n",
+ " <td>3/28/2019</td>\n",
+ " <td>JTHDU1EF3G5020098</td>\n",
+ " <td>No</td>\n",
+ " <td>Yes</td>\n",
+ " <td>Test Driver</td>\n",
+ " <td>Street</td>\n",
+ " <td>Safety Driver proactive disengagement.</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>freq</th>\n",
+ " <td>2947</td>\n",
+ " <td>2947</td>\n",
+ " <td>59</td>\n",
+ " <td>900</td>\n",
+ " <td>4369</td>\n",
+ " <td>4934</td>\n",
+ " <td>6037</td>\n",
+ " <td>4668</td>\n",
+ " <td>1780</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "</div>"
+ ],
+ "text/plain": [
+ " Manufacturer Permit Number DATE VIN NUMBER \\\n",
+ "count 8885 8885 8884 8884 \n",
+ "unique 28 27 3711 289 \n",
+ "top Toyota Research Institute AVT050 3/28/2019 JTHDU1EF3G5020098 \n",
+ "freq 2947 2947 59 900 \n",
+ "\n",
+ " VEHICLE IS CAPABLE OF OPERATING WITHOUT A DRIVER\\n(Yes or No) \\\n",
+ "count 8884 \n",
+ "unique 5 \n",
+ "top No \n",
+ "freq 4369 \n",
+ "\n",
+ " DRIVER PRESENT\\n(Yes or No) \\\n",
+ "count 8884 \n",
+ "unique 4 \n",
+ "top Yes \n",
+ "freq 4934 \n",
+ "\n",
+ " DISENGAGEMENT INITIATED BY\\n(AV System, Test Driver, Remote Operator, or Passenger) \\\n",
+ "count 8884 \n",
+ "unique 4 \n",
+ "top Test Driver \n",
+ "freq 6037 \n",
+ "\n",
+ " DISENGAGEMENT\\nLOCATION\\n(Interstate, Freeway, Highway, Rural Road, Street, or Parking Facility) \\\n",
+ "count 8884 \n",
+ "unique 11 \n",
+ "top Street \n",
+ "freq 4668 \n",
+ "\n",
+ " DESCRIPTION OF FACTS CAUSING DISENGAGEMENT \n",
+ "count 8884 \n",
+ "unique 469 \n",
+ "top Safety Driver proactive disengagement. \n",
+ "freq 1780 "
+ ]
+ },
+ "execution_count": 81,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "raw_data.describe(include=\"all\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 82,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "raw_data.rename(columns = {'VEHICLE IS CAPABLE OF OPERATING WITHOUT A DRIVER\\n(Yes or No)':'OPERATING WITHOUT DRIVER', 'DRIVER PRESENT\\n(Yes or No)':'DRIVER PRESENT', 'DISENGAGEMENT INITIATED BY\\n(AV System, Test Driver, Remote Operator, or Passenger)':'DISENGAGEMENT INITIATED BY', 'DISENGAGEMENT\\nLOCATION\\n(Interstate, Freeway, Highway, Rural Road, Street, or Parking Facility)':'DISENGAGEMENT LOCATION', 'DESCRIPTION OF FACTS CAUSING DISENGAGEMENT':'FACTS CAUSING DISENGAGEMENT'}, inplace = True) "
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Missing Values"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 83,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "Manufacturer 0\n",
+ "Permit Number 0\n",
+ "DATE 1\n",
+ "VIN NUMBER 1\n",
+ "OPERATING WITHOUT DRIVER 1\n",
+ "DRIVER PRESENT 1\n",
+ "DISENGAGEMENT INITIATED BY 1\n",
+ "DISENGAGEMENT LOCATION 1\n",
+ "FACTS CAUSING DISENGAGEMENT 1\n",
+ "dtype: int64"
+ ]
+ },
+ "execution_count": 83,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "raw_data.isnull().sum()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 84,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "Manufacturer 0\n",
+ "Permit Number 0\n",
+ "DATE 0\n",
+ "VIN NUMBER 0\n",
+ "OPERATING WITHOUT DRIVER 0\n",
+ "DRIVER PRESENT 0\n",
+ "DISENGAGEMENT INITIATED BY 0\n",
+ "DISENGAGEMENT LOCATION 0\n",
+ "FACTS CAUSING DISENGAGEMENT 0\n",
+ "dtype: int64"
+ ]
+ },
+ "execution_count": 84,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "data_no_mv=raw_data.dropna(axis=0)\n",
+ "data_no_mv.isnull().sum()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 85,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "<div>\n",
+ "<style scoped>\n",
+ " .dataframe tbody tr th:only-of-type {\n",
+ " vertical-align: middle;\n",
+ " }\n",
+ "\n",
+ " .dataframe tbody tr th {\n",
+ " vertical-align: top;\n",
+ " }\n",
+ "\n",
+ " .dataframe thead th {\n",
+ " text-align: right;\n",
+ " }\n",
+ "</style>\n",
+ "<table border=\"1\" class=\"dataframe\">\n",
+ " <thead>\n",
+ " <tr style=\"text-align: right;\">\n",
+ " <th></th>\n",
+ " <th>Manufacturer</th>\n",
+ " <th>Permit Number</th>\n",
+ " <th>DATE</th>\n",
+ " <th>VIN NUMBER</th>\n",
+ " <th>OPERATING WITHOUT DRIVER</th>\n",
+ " <th>DRIVER PRESENT</th>\n",
+ " <th>DISENGAGEMENT INITIATED BY</th>\n",
+ " <th>DISENGAGEMENT LOCATION</th>\n",
+ " <th>FACTS CAUSING DISENGAGEMENT</th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " <tr>\n",
+ " <th>count</th>\n",
+ " <td>8884</td>\n",
+ " <td>8884</td>\n",
+ " <td>8884</td>\n",
+ " <td>8884</td>\n",
+ " <td>8884</td>\n",
+ " <td>8884</td>\n",
+ " <td>8884</td>\n",
+ " <td>8884</td>\n",
+ " <td>8884</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>unique</th>\n",
+ " <td>27</td>\n",
+ " <td>26</td>\n",
+ " <td>3711</td>\n",
+ " <td>289</td>\n",
+ " <td>5</td>\n",
+ " <td>4</td>\n",
+ " <td>4</td>\n",
+ " <td>11</td>\n",
+ " <td>469</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>top</th>\n",
+ " <td>Toyota Research Institute</td>\n",
+ " <td>AVT050</td>\n",
+ " <td>3/28/2019</td>\n",
+ " <td>JTHDU1EF3G5020098</td>\n",
+ " <td>No</td>\n",
+ " <td>Yes</td>\n",
+ " <td>Test Driver</td>\n",
+ " <td>Street</td>\n",
+ " <td>Safety Driver proactive disengagement.</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>freq</th>\n",
+ " <td>2947</td>\n",
+ " <td>2947</td>\n",
+ " <td>59</td>\n",
+ " <td>900</td>\n",
+ " <td>4369</td>\n",
+ " <td>4934</td>\n",
+ " <td>6037</td>\n",
+ " <td>4668</td>\n",
+ " <td>1780</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "</div>"
+ ],
+ "text/plain": [
+ " Manufacturer Permit Number DATE VIN NUMBER \\\n",
+ "count 8884 8884 8884 8884 \n",
+ "unique 27 26 3711 289 \n",
+ "top Toyota Research Institute AVT050 3/28/2019 JTHDU1EF3G5020098 \n",
+ "freq 2947 2947 59 900 \n",
+ "\n",
+ " OPERATING WITHOUT DRIVER DRIVER PRESENT DISENGAGEMENT INITIATED BY \\\n",
+ "count 8884 8884 8884 \n",
+ "unique 5 4 4 \n",
+ "top No Yes Test Driver \n",
+ "freq 4369 4934 6037 \n",
+ "\n",
+ " DISENGAGEMENT LOCATION FACTS CAUSING DISENGAGEMENT \n",
+ "count 8884 8884 \n",
+ "unique 11 469 \n",
+ "top Street Safety Driver proactive disengagement. \n",
+ "freq 4668 1780 "
+ ]
+ },
+ "execution_count": 85,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "data_no_mv.describe(include='all')"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Data preparation and labeling"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 86,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "DISENGAGEMENT INITIATED BY\n",
+ "Test Driver 6037\n",
+ "AV System 2698\n",
+ "Vehicle Operator 81\n",
+ "Test driver 68\n",
+ "Name: count, dtype: int64"
+ ]
+ },
+ "execution_count": 86,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "data_no_mv['DISENGAGEMENT INITIATED BY'].value_counts()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 87,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "469"
+ ]
+ },
+ "execution_count": 87,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "data_no_mv['FACTS CAUSING DISENGAGEMENT'].nunique()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 88,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "<div>\n",
+ "<style scoped>\n",
+ " .dataframe tbody tr th:only-of-type {\n",
+ " vertical-align: middle;\n",
+ " }\n",
+ "\n",
+ " .dataframe tbody tr th {\n",
+ " vertical-align: top;\n",
+ " }\n",
+ "\n",
+ " .dataframe thead th {\n",
+ " text-align: right;\n",
+ " }\n",
+ "</style>\n",
+ "<table border=\"1\" class=\"dataframe\">\n",
+ " <thead>\n",
+ " <tr style=\"text-align: right;\">\n",
+ " <th></th>\n",
+ " <th>Manufacturer</th>\n",
+ " <th>Permit Number</th>\n",
+ " <th>DATE</th>\n",
+ " <th>VIN NUMBER</th>\n",
+ " <th>OPERATING WITHOUT DRIVER</th>\n",
+ " <th>DRIVER PRESENT</th>\n",
+ " <th>DISENGAGEMENT INITIATED BY</th>\n",
+ " <th>DISENGAGEMENT LOCATION</th>\n",
+ " <th>FACTS CAUSING DISENGAGEMENT</th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " <tr>\n",
+ " <th>0</th>\n",
+ " <td>AImotive Inc.</td>\n",
+ " <td>AVT003</td>\n",
+ " <td>12.06.2018</td>\n",
+ " <td>JTDKN3DU5A1092792</td>\n",
+ " <td>No</td>\n",
+ " <td>Yes</td>\n",
+ " <td>Test Driver</td>\n",
+ " <td>Freeway</td>\n",
+ " <td>Lane change maneuver: risk of lane departure, ...</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>1</th>\n",
+ " <td>AImotive Inc.</td>\n",
+ " <td>AVT003</td>\n",
+ " <td>12.10.2018</td>\n",
+ " <td>JTDKN3DU5A1092792</td>\n",
+ " <td>No</td>\n",
+ " <td>Yes</td>\n",
+ " <td>Test Driver</td>\n",
+ " <td>Freeway</td>\n",
+ " <td>Lane change maneuver: risk of lane departure, ...</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>2</th>\n",
+ " <td>AImotive Inc.</td>\n",
+ " <td>AVT003</td>\n",
+ " <td>12.10.2018</td>\n",
+ " <td>JTDKN3DU5A1092792</td>\n",
+ " <td>No</td>\n",
+ " <td>Yes</td>\n",
+ " <td>Test Driver</td>\n",
+ " <td>Freeway</td>\n",
+ " <td>Lane change maneuver: risk of lane departure, ...</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>3</th>\n",
+ " <td>AImotive Inc.</td>\n",
+ " <td>AVT003</td>\n",
+ " <td>04.23.2019</td>\n",
+ " <td>JTDKN3DU5A1092792</td>\n",
+ " <td>No</td>\n",
+ " <td>Yes</td>\n",
+ " <td>Test Driver</td>\n",
+ " <td>Freeway</td>\n",
+ " <td>Lane change maneuver: risk of lane departure, ...</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>4</th>\n",
+ " <td>AImotive Inc.</td>\n",
+ " <td>AVT003</td>\n",
+ " <td>05.14.2019</td>\n",
+ " <td>JTDKN3DU5A1092792</td>\n",
+ " <td>No</td>\n",
+ " <td>Yes</td>\n",
+ " <td>Test Driver</td>\n",
+ " <td>Freeway</td>\n",
+ " <td>Lane change maneuver to the exit lane: risk of...</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "</div>"
+ ],
+ "text/plain": [
+ " Manufacturer Permit Number DATE VIN NUMBER \\\n",
+ "0 AImotive Inc. AVT003 12.06.2018 JTDKN3DU5A1092792 \n",
+ "1 AImotive Inc. AVT003 12.10.2018 JTDKN3DU5A1092792 \n",
+ "2 AImotive Inc. AVT003 12.10.2018 JTDKN3DU5A1092792 \n",
+ "3 AImotive Inc. AVT003 04.23.2019 JTDKN3DU5A1092792 \n",
+ "4 AImotive Inc. AVT003 05.14.2019 JTDKN3DU5A1092792 \n",
+ "\n",
+ " OPERATING WITHOUT DRIVER DRIVER PRESENT DISENGAGEMENT INITIATED BY \\\n",
+ "0 No Yes Test Driver \n",
+ "1 No Yes Test Driver \n",
+ "2 No Yes Test Driver \n",
+ "3 No Yes Test Driver \n",
+ "4 No Yes Test Driver \n",
+ "\n",
+ " DISENGAGEMENT LOCATION FACTS CAUSING DISENGAGEMENT \n",
+ "0 Freeway Lane change maneuver: risk of lane departure, ... \n",
+ "1 Freeway Lane change maneuver: risk of lane departure, ... \n",
+ "2 Freeway Lane change maneuver: risk of lane departure, ... \n",
+ "3 Freeway Lane change maneuver: risk of lane departure, ... \n",
+ "4 Freeway Lane change maneuver to the exit lane: risk of... "
+ ]
+ },
+ "execution_count": 88,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "data_no_mv.head()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 89,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "FACTS CAUSING DISENGAGEMENT\n",
+ "Safety Driver proactive disengagement. 1780\n",
+ "Disengage for unwanted maneuver of the vehicle caused by a planning discrepancy while generating an appropriate trajectory 805\n",
+ "Automatic disengagement caused by planner fault. 742\n",
+ "Disengage due to operator discomfort 636\n",
+ "Disengage for a software fault due to a potential performance issue with a software component of the self-driving system (including third party software components) 482\n",
+ " ... \n",
+ "Planning Logic: planner inadequately yields for cross traffic agent with right-of-way 1\n",
+ "Planning Logic: planned trajectory fails to avoid vehicle stopped ahead intersection 1\n",
+ "Object Perception: inaccurate perception of animal slowly crossing road leads to planned trajectory overlap 1\n",
+ "Planning Logic: incorrect behavior prediction for oncoming vehicle results in a planned trajectory that overlaps with the vehicle 1\n",
+ "Planning discrepancy; system planned incorrect trajectory to avoid oncoming traffic 1\n",
+ "Name: count, Length: 469, dtype: int64"
+ ]
+ },
+ "execution_count": 89,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "data_no_mv['FACTS CAUSING DISENGAGEMENT'].value_counts()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 90,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "DISENGAGEMENT INITIATED BY\n",
+ "Test Driver 6037\n",
+ "AV System 2698\n",
+ "Vehicle Operator 81\n",
+ "Test driver 68\n",
+ "Name: count, dtype: int64"
+ ]
+ },
+ "execution_count": 90,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "data_no_mv['DISENGAGEMENT INITIATED BY'].value_counts()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 91,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "data_reduced = data_no_mv.loc[0:1999, :]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 92,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "<class 'pandas.core.frame.DataFrame'>\n",
+ "Index: 2000 entries, 0 to 1999\n",
+ "Data columns (total 9 columns):\n",
+ " # Column Non-Null Count Dtype \n",
+ "--- ------ -------------- ----- \n",
+ " 0 Manufacturer 2000 non-null object\n",
+ " 1 Permit Number 2000 non-null object\n",
+ " 2 DATE 2000 non-null object\n",
+ " 3 VIN NUMBER 2000 non-null object\n",
+ " 4 OPERATING WITHOUT DRIVER 2000 non-null object\n",
+ " 5 DRIVER PRESENT 2000 non-null object\n",
+ " 6 DISENGAGEMENT INITIATED BY 2000 non-null object\n",
+ " 7 DISENGAGEMENT LOCATION 2000 non-null object\n",
+ " 8 FACTS CAUSING DISENGAGEMENT 2000 non-null object\n",
+ "dtypes: object(9)\n",
+ "memory usage: 156.2+ KB\n"
+ ]
+ }
+ ],
+ "source": [
+ "data_reduced.info()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 93,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "92"
+ ]
+ },
+ "execution_count": 93,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "data_reduced['FACTS CAUSING DISENGAGEMENT'].nunique()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 94,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "C:\\Users\\ar\\AppData\\Local\\Temp\\ipykernel_3376\\3061903378.py:1: SettingWithCopyWarning: \n",
+ "A value is trying to be set on a copy of a slice from a DataFrame\n",
+ "\n",
+ "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+ " data_reduced.drop_duplicates(subset =\"FACTS CAUSING DISENGAGEMENT\",\n"
+ ]
+ }
+ ],
+ "source": [
+ "data_reduced.drop_duplicates(subset =\"FACTS CAUSING DISENGAGEMENT\", \n",
+ " keep = 'first', inplace = True) "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 95,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "data_reduced = data_reduced.reset_index()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 96,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "data_reduced['FACTS CAUSING DISENGAGEMENT'] = data_reduced['FACTS CAUSING DISENGAGEMENT'].astype('str')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 97,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "dtype('O')"
+ ]
+ },
+ "execution_count": 97,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "data_reduced['FACTS CAUSING DISENGAGEMENT'].dtype"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 98,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import re"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 99,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "software_keywords = [\"software performance\", \"software fault\", \"software discrepancy\"\n",
+ " \"trajectory planning\", \"planning discrepancy\", \"planning error\",\n",
+ " \"wrong lane change suggestion\", \"wrong lane association\", \"data recording\",\n",
+ " \"improper lane-change plan\", \"undesirable manuever\", \"undesirable yielding maneuver\",\n",
+ " \"outside of rate requirements\", \"merged poorly\", \"mapping issue\", \"software issue\",\n",
+ " \"poor trajectory across lanes\", \"incorrect assessment\", \"incorrect behavior\",\n",
+ " \"unprotected\", \"Poor lane change\", \"very wide\", \"wrong object prediction\", \"undesired motion\",\n",
+ " \"unwanted maneuver\", \"perception discrepancy\", \"ghost object prediction\",\n",
+ " \"driving faster than driver expected\", \"expected path\",\n",
+ " \"not initialized correctly\", \"software module\", \"perception mismatch\", \"estimation\",\n",
+ " \"planner fault\", \"unstable\"]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 100,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "C:\\Users\\ar\\AppData\\Local\\Temp\\ipykernel_3376\\1320408372.py:1: SettingWithCopyWarning: \n",
+ "A value is trying to be set on a copy of a slice from a DataFrame.\n",
+ "Try using .loc[row_indexer,col_indexer] = value instead\n",
+ "\n",
+ "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+ " data_no_mv.loc[data_no_mv['FACTS CAUSING DISENGAGEMENT'].str.contains('|'.join(software_keywords), na=False, case=False)\n"
+ ]
+ }
+ ],
+ "source": [
+ "data_no_mv.loc[data_no_mv['FACTS CAUSING DISENGAGEMENT'].str.contains('|'.join(software_keywords), na=False, case=False)\n",
+ " , 'Problem class'] = \"Software\" "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 101,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "hardware_keywords = [\"hardware performance\", \"hardware diagnostics\", \"controls diagnostics\", \"actor\", \n",
+ " \"yield to other actors\", \"Hardware irregularity\", \"weather conditions\", \"Autobox\", \n",
+ " \"performance issue with a hardware component\"]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 102,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "data_no_mv.loc[data_no_mv['FACTS CAUSING DISENGAGEMENT'].str.contains('|'.join(hardware_keywords), na=False, case=False)\n",
+ " , 'Problem class'] = \"Hardware\" "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 103,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "soft_hardware_keywords = [\"timed out\", \"timeout\", \"too long\", \"incorrect detection\", \"Lost track\", \"Localization\", \n",
+ " \"geo-location related\", \"unsuccessful right turn\", \"unsuccessful left turn\", \"system\",\n",
+ " \"traffic conditions\", \"failed to detect an object correctly\", \" took longer than expected\",\n",
+ " \"main computer froze\", \"not braking correctly\", \"not speeding up correctly\",\n",
+ " \"not turning enough\", \"not slowing down enough\", \"didn't detect\", \"Sensor Fusion discrepancy\",\n",
+ " \"did not meet expectation\"]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 104,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "data_no_mv.loc[data_no_mv['FACTS CAUSING DISENGAGEMENT'].str.contains('|'.join(soft_hardware_keywords), na=False, case=False)\n",
+ " , 'Problem class'] = \"Software/Hardware\" "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 105,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "Traffic_ctrl_keywords = [\"unstable target lane\", \"Traffic light error\", \"Stop sign error\"]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 106,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "data_no_mv.loc[data_no_mv['FACTS CAUSING DISENGAGEMENT'].str.contains('|'.join(Traffic_ctrl_keywords), na=False, case=False)\n",
+ " , 'Problem class'] = \"Traffic control objects\" "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 107,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "road_user_keywords = [\"reckless driver\", \"behaving road user\", \"other road user\"]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 108,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "data_no_mv.loc[data_no_mv['FACTS CAUSING DISENGAGEMENT'].str.contains('|'.join(road_user_keywords), na=False, case=False)\n",
+ " , 'Problem class'] = \"Other road user\" "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 109,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "external_influences = [\"obstruction\", \"encroachment\", \"occluded view\", \"surface conditions\", \"wheater\"]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 110,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "data_no_mv.loc[data_no_mv['FACTS CAUSING DISENGAGEMENT'].str.contains('|'.join(external_influences), na=False, case=False)\n",
+ " , 'Problem class'] = \"External influences\" "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 111,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "data_no_mv.loc[data_no_mv['Problem class'].isnull()\n",
+ " , 'Problem class'] = \"Other problems\" "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 112,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "<div>\n",
+ "<style scoped>\n",
+ " .dataframe tbody tr th:only-of-type {\n",
+ " vertical-align: middle;\n",
+ " }\n",
+ "\n",
+ " .dataframe tbody tr th {\n",
+ " vertical-align: top;\n",
+ " }\n",
+ "\n",
+ " .dataframe thead th {\n",
+ " text-align: right;\n",
+ " }\n",
+ "</style>\n",
+ "<table border=\"1\" class=\"dataframe\">\n",
+ " <thead>\n",
+ " <tr style=\"text-align: right;\">\n",
+ " <th></th>\n",
+ " <th>Manufacturer</th>\n",
+ " <th>Permit Number</th>\n",
+ " <th>DATE</th>\n",
+ " <th>VIN NUMBER</th>\n",
+ " <th>OPERATING WITHOUT DRIVER</th>\n",
+ " <th>DRIVER PRESENT</th>\n",
+ " <th>DISENGAGEMENT INITIATED BY</th>\n",
+ " <th>DISENGAGEMENT LOCATION</th>\n",
+ " <th>FACTS CAUSING DISENGAGEMENT</th>\n",
+ " <th>Problem class</th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " <tr>\n",
+ " <th>0</th>\n",
+ " <td>AImotive Inc.</td>\n",
+ " <td>AVT003</td>\n",
+ " <td>12.06.2018</td>\n",
+ " <td>JTDKN3DU5A1092792</td>\n",
+ " <td>No</td>\n",
+ " <td>Yes</td>\n",
+ " <td>Test Driver</td>\n",
+ " <td>Freeway</td>\n",
+ " <td>Lane change maneuver: risk of lane departure, ...</td>\n",
+ " <td>Traffic control objects</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>1</th>\n",
+ " <td>AImotive Inc.</td>\n",
+ " <td>AVT003</td>\n",
+ " <td>12.10.2018</td>\n",
+ " <td>JTDKN3DU5A1092792</td>\n",
+ " <td>No</td>\n",
+ " <td>Yes</td>\n",
+ " <td>Test Driver</td>\n",
+ " <td>Freeway</td>\n",
+ " <td>Lane change maneuver: risk of lane departure, ...</td>\n",
+ " <td>Traffic control objects</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>2</th>\n",
+ " <td>AImotive Inc.</td>\n",
+ " <td>AVT003</td>\n",
+ " <td>12.10.2018</td>\n",
+ " <td>JTDKN3DU5A1092792</td>\n",
+ " <td>No</td>\n",
+ " <td>Yes</td>\n",
+ " <td>Test Driver</td>\n",
+ " <td>Freeway</td>\n",
+ " <td>Lane change maneuver: risk of lane departure, ...</td>\n",
+ " <td>Traffic control objects</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>3</th>\n",
+ " <td>AImotive Inc.</td>\n",
+ " <td>AVT003</td>\n",
+ " <td>04.23.2019</td>\n",
+ " <td>JTDKN3DU5A1092792</td>\n",
+ " <td>No</td>\n",
+ " <td>Yes</td>\n",
+ " <td>Test Driver</td>\n",
+ " <td>Freeway</td>\n",
+ " <td>Lane change maneuver: risk of lane departure, ...</td>\n",
+ " <td>Other problems</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>4</th>\n",
+ " <td>AImotive Inc.</td>\n",
+ " <td>AVT003</td>\n",
+ " <td>05.14.2019</td>\n",
+ " <td>JTDKN3DU5A1092792</td>\n",
+ " <td>No</td>\n",
+ " <td>Yes</td>\n",
+ " <td>Test Driver</td>\n",
+ " <td>Freeway</td>\n",
+ " <td>Lane change maneuver to the exit lane: risk of...</td>\n",
+ " <td>Software</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "</div>"
+ ],
+ "text/plain": [
+ " Manufacturer Permit Number DATE VIN NUMBER \\\n",
+ "0 AImotive Inc. AVT003 12.06.2018 JTDKN3DU5A1092792 \n",
+ "1 AImotive Inc. AVT003 12.10.2018 JTDKN3DU5A1092792 \n",
+ "2 AImotive Inc. AVT003 12.10.2018 JTDKN3DU5A1092792 \n",
+ "3 AImotive Inc. AVT003 04.23.2019 JTDKN3DU5A1092792 \n",
+ "4 AImotive Inc. AVT003 05.14.2019 JTDKN3DU5A1092792 \n",
+ "\n",
+ " OPERATING WITHOUT DRIVER DRIVER PRESENT DISENGAGEMENT INITIATED BY \\\n",
+ "0 No Yes Test Driver \n",
+ "1 No Yes Test Driver \n",
+ "2 No Yes Test Driver \n",
+ "3 No Yes Test Driver \n",
+ "4 No Yes Test Driver \n",
+ "\n",
+ " DISENGAGEMENT LOCATION FACTS CAUSING DISENGAGEMENT \\\n",
+ "0 Freeway Lane change maneuver: risk of lane departure, ... \n",
+ "1 Freeway Lane change maneuver: risk of lane departure, ... \n",
+ "2 Freeway Lane change maneuver: risk of lane departure, ... \n",
+ "3 Freeway Lane change maneuver: risk of lane departure, ... \n",
+ "4 Freeway Lane change maneuver to the exit lane: risk of... \n",
+ "\n",
+ " Problem class \n",
+ "0 Traffic control objects \n",
+ "1 Traffic control objects \n",
+ "2 Traffic control objects \n",
+ "3 Other problems \n",
+ "4 Software "
+ ]
+ },
+ "execution_count": 112,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "data_no_mv.head()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Classification model"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 113,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "data_preprocessed = data_no_mv.copy()\n",
+ "data_preprocessed['Problem class']=data_preprocessed['Problem class'].map(\n",
+ " {'Software':0,'Hardware':1,'Software/Hardware':2,\n",
+ " 'Traffic control objects':3,'Other road user':4, 'External influences':5,\n",
+ " 'Other problems':6})\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 114,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "<div>\n",
+ "<style scoped>\n",
+ " .dataframe tbody tr th:only-of-type {\n",
+ " vertical-align: middle;\n",
+ " }\n",
+ "\n",
+ " .dataframe tbody tr th {\n",
+ " vertical-align: top;\n",
+ " }\n",
+ "\n",
+ " .dataframe thead th {\n",
+ " text-align: right;\n",
+ " }\n",
+ "</style>\n",
+ "<table border=\"1\" class=\"dataframe\">\n",
+ " <thead>\n",
+ " <tr style=\"text-align: right;\">\n",
+ " <th></th>\n",
+ " <th>Manufacturer</th>\n",
+ " <th>Permit Number</th>\n",
+ " <th>DATE</th>\n",
+ " <th>VIN NUMBER</th>\n",
+ " <th>OPERATING WITHOUT DRIVER</th>\n",
+ " <th>DRIVER PRESENT</th>\n",
+ " <th>DISENGAGEMENT INITIATED BY</th>\n",
+ " <th>DISENGAGEMENT LOCATION</th>\n",
+ " <th>FACTS CAUSING DISENGAGEMENT</th>\n",
+ " <th>Problem class</th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " <tr>\n",
+ " <th>0</th>\n",
+ " <td>AImotive Inc.</td>\n",
+ " <td>AVT003</td>\n",
+ " <td>12.06.2018</td>\n",
+ " <td>JTDKN3DU5A1092792</td>\n",
+ " <td>No</td>\n",
+ " <td>Yes</td>\n",
+ " <td>Test Driver</td>\n",
+ " <td>Freeway</td>\n",
+ " <td>Lane change maneuver: risk of lane departure, ...</td>\n",
+ " <td>3</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>1</th>\n",
+ " <td>AImotive Inc.</td>\n",
+ " <td>AVT003</td>\n",
+ " <td>12.10.2018</td>\n",
+ " <td>JTDKN3DU5A1092792</td>\n",
+ " <td>No</td>\n",
+ " <td>Yes</td>\n",
+ " <td>Test Driver</td>\n",
+ " <td>Freeway</td>\n",
+ " <td>Lane change maneuver: risk of lane departure, ...</td>\n",
+ " <td>3</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>2</th>\n",
+ " <td>AImotive Inc.</td>\n",
+ " <td>AVT003</td>\n",
+ " <td>12.10.2018</td>\n",
+ " <td>JTDKN3DU5A1092792</td>\n",
+ " <td>No</td>\n",
+ " <td>Yes</td>\n",
+ " <td>Test Driver</td>\n",
+ " <td>Freeway</td>\n",
+ " <td>Lane change maneuver: risk of lane departure, ...</td>\n",
+ " <td>3</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>3</th>\n",
+ " <td>AImotive Inc.</td>\n",
+ " <td>AVT003</td>\n",
+ " <td>04.23.2019</td>\n",
+ " <td>JTDKN3DU5A1092792</td>\n",
+ " <td>No</td>\n",
+ " <td>Yes</td>\n",
+ " <td>Test Driver</td>\n",
+ " <td>Freeway</td>\n",
+ " <td>Lane change maneuver: risk of lane departure, ...</td>\n",
+ " <td>6</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>4</th>\n",
+ " <td>AImotive Inc.</td>\n",
+ " <td>AVT003</td>\n",
+ " <td>05.14.2019</td>\n",
+ " <td>JTDKN3DU5A1092792</td>\n",
+ " <td>No</td>\n",
+ " <td>Yes</td>\n",
+ " <td>Test Driver</td>\n",
+ " <td>Freeway</td>\n",
+ " <td>Lane change maneuver to the exit lane: risk of...</td>\n",
+ " <td>0</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "</div>"
+ ],
+ "text/plain": [
+ " Manufacturer Permit Number DATE VIN NUMBER \\\n",
+ "0 AImotive Inc. AVT003 12.06.2018 JTDKN3DU5A1092792 \n",
+ "1 AImotive Inc. AVT003 12.10.2018 JTDKN3DU5A1092792 \n",
+ "2 AImotive Inc. AVT003 12.10.2018 JTDKN3DU5A1092792 \n",
+ "3 AImotive Inc. AVT003 04.23.2019 JTDKN3DU5A1092792 \n",
+ "4 AImotive Inc. AVT003 05.14.2019 JTDKN3DU5A1092792 \n",
+ "\n",
+ " OPERATING WITHOUT DRIVER DRIVER PRESENT DISENGAGEMENT INITIATED BY \\\n",
+ "0 No Yes Test Driver \n",
+ "1 No Yes Test Driver \n",
+ "2 No Yes Test Driver \n",
+ "3 No Yes Test Driver \n",
+ "4 No Yes Test Driver \n",
+ "\n",
+ " DISENGAGEMENT LOCATION FACTS CAUSING DISENGAGEMENT \\\n",
+ "0 Freeway Lane change maneuver: risk of lane departure, ... \n",
+ "1 Freeway Lane change maneuver: risk of lane departure, ... \n",
+ "2 Freeway Lane change maneuver: risk of lane departure, ... \n",
+ "3 Freeway Lane change maneuver: risk of lane departure, ... \n",
+ "4 Freeway Lane change maneuver to the exit lane: risk of... \n",
+ "\n",
+ " Problem class \n",
+ "0 3 \n",
+ "1 3 \n",
+ "2 3 \n",
+ "3 6 \n",
+ "4 0 "
+ ]
+ },
+ "execution_count": 114,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "data_preprocessed.head()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 115,
+ "metadata": {
+ "scrolled": true
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "<class 'pandas.core.frame.DataFrame'>\n",
+ "Index: 8884 entries, 0 to 8884\n",
+ "Data columns (total 10 columns):\n",
+ " # Column Non-Null Count Dtype \n",
+ "--- ------ -------------- ----- \n",
+ " 0 Manufacturer 8884 non-null object\n",
+ " 1 Permit Number 8884 non-null object\n",
+ " 2 DATE 8884 non-null object\n",
+ " 3 VIN NUMBER 8884 non-null object\n",
+ " 4 OPERATING WITHOUT DRIVER 8884 non-null object\n",
+ " 5 DRIVER PRESENT 8884 non-null object\n",
+ " 6 DISENGAGEMENT INITIATED BY 8884 non-null object\n",
+ " 7 DISENGAGEMENT LOCATION 8884 non-null object\n",
+ " 8 FACTS CAUSING DISENGAGEMENT 8884 non-null object\n",
+ " 9 Problem class 8884 non-null int64 \n",
+ "dtypes: int64(1), object(9)\n",
+ "memory usage: 1021.5+ KB\n"
+ ]
+ }
+ ],
+ "source": [
+ "data_preprocessed.info()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 116,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "<div>\n",
+ "<style scoped>\n",
+ " .dataframe tbody tr th:only-of-type {\n",
+ " vertical-align: middle;\n",
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+ "<table border=\"1\" class=\"dataframe\">\n",
+ " <thead>\n",
+ " <tr style=\"text-align: right;\">\n",
+ " <th></th>\n",
+ " <th>Problem class</th>\n",
+ " <th>Manufacturer_Apple Inc.</th>\n",
+ " <th>Manufacturer_Aurora Innovation, Inc.</th>\n",
+ " <th>Manufacturer_AutoX Technologies, Inc.</th>\n",
+ " <th>Manufacturer_BMW of North America</th>\n",
+ " <th>Manufacturer_Baidu USA LLC</th>\n",
+ " <th>Manufacturer_CRUISE LLC</th>\n",
+ " <th>Manufacturer_Drive.ai Inc</th>\n",
+ " <th>Manufacturer_Lyft</th>\n",
+ " <th>Manufacturer_Mercedes-Benz Research & Development North America, Inc.</th>\n",
+ " <th>...</th>\n",
+ " <th>FACTS CAUSING DISENGAGEMENT_precautionary takeover to address planning, \\nprecautionary takeover to address perception, \\nother road user behaving poorly</th>\n",
+ " <th>FACTS CAUSING DISENGAGEMENT_precautionary takeover to address planning, \\nprecautionary takeover to address perception, AV made unsuccessful left turn</th>\n",
+ " <th>FACTS CAUSING DISENGAGEMENT_precautionary takeover to address planning, \\nprecautionary takeover to address perception, third party lane encroachment</th>\n",
+ " <th>FACTS CAUSING DISENGAGEMENT_precautionary takeover to address planning, \\nprecautionary takeover to address perception, third party lane obstruction</th>\n",
+ " <th>FACTS CAUSING DISENGAGEMENT_precautionary takeover to address planning, AV lane change issues</th>\n",
+ " <th>FACTS CAUSING DISENGAGEMENT_precautionary takeover to address planning, AV made unsuccessful left turn</th>\n",
+ " <th>FACTS CAUSING DISENGAGEMENT_precautionary takeover to address planning, other road user behaving poorly</th>\n",
+ " <th>FACTS CAUSING DISENGAGEMENT_precautionary takeover to address planning, third party lane encroachment</th>\n",
+ " <th>FACTS CAUSING DISENGAGEMENT_precautionary takeover to address planning, third party lane obstruction</th>\n",
+ " <th>FACTS CAUSING DISENGAGEMENT_prediction discrepancy, a vehicle in the front was backing up, ego was not able to predict this behavior correctly.</th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
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+ " <tr>\n",
+ " <th>1</th>\n",
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+ " <td>False</td>\n",
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+ " <td>False</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>2</th>\n",
+ " <td>3</td>\n",
+ " <td>False</td>\n",
+ " <td>False</td>\n",
+ " <td>False</td>\n",
+ " <td>False</td>\n",
+ " <td>False</td>\n",
+ " <td>False</td>\n",
+ " <td>False</td>\n",
+ " <td>False</td>\n",
+ " <td>False</td>\n",
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+ " </tr>\n",
+ " <tr>\n",
+ " <th>3</th>\n",
+ " <td>6</td>\n",
+ " <td>False</td>\n",
+ " <td>False</td>\n",
+ " <td>False</td>\n",
+ " <td>False</td>\n",
+ " <td>False</td>\n",
+ " <td>False</td>\n",
+ " <td>False</td>\n",
+ " <td>False</td>\n",
+ " <td>False</td>\n",
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+ " <td>False</td>\n",
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+ " <td>False</td>\n",
+ " <td>False</td>\n",
+ " <td>False</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>4</th>\n",
+ " <td>0</td>\n",
+ " <td>False</td>\n",
+ " <td>False</td>\n",
+ " <td>False</td>\n",
+ " <td>False</td>\n",
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+ " <td>False</td>\n",
+ " <td>False</td>\n",
+ " <td>False</td>\n",
+ " <td>False</td>\n",
+ " <td>...</td>\n",
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+ " <td>False</td>\n",
+ " <td>False</td>\n",
+ " <td>False</td>\n",
+ " <td>False</td>\n",
+ " <td>False</td>\n",
+ " <td>False</td>\n",
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+ " <td>False</td>\n",
+ " <td>False</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "<p>5 rows × 4538 columns</p>\n",
+ "</div>"
+ ],
+ "text/plain": [
+ " Problem class Manufacturer_Apple Inc. \\\n",
+ "0 3 False \n",
+ "1 3 False \n",
+ "2 3 False \n",
+ "3 6 False \n",
+ "4 0 False \n",
+ "\n",
+ " Manufacturer_Aurora Innovation, Inc. \\\n",
+ "0 False \n",
+ "1 False \n",
+ "2 False \n",
+ "3 False \n",
+ "4 False \n",
+ "\n",
+ " Manufacturer_AutoX Technologies, Inc. Manufacturer_BMW of North America \\\n",
+ "0 False False \n",
+ "1 False False \n",
+ "2 False False \n",
+ "3 False False \n",
+ "4 False False \n",
+ "\n",
+ " Manufacturer_Baidu USA LLC Manufacturer_CRUISE LLC \\\n",
+ "0 False False \n",
+ "1 False False \n",
+ "2 False False \n",
+ "3 False False \n",
+ "4 False False \n",
+ "\n",
+ " Manufacturer_Drive.ai Inc Manufacturer_Lyft \\\n",
+ "0 False False \n",
+ "1 False False \n",
+ "2 False False \n",
+ "3 False False \n",
+ "4 False False \n",
+ "\n",
+ " Manufacturer_Mercedes-Benz Research & Development North America, Inc. ... \\\n",
+ "0 False ... \n",
+ "1 False ... \n",
+ "2 False ... \n",
+ "3 False ... \n",
+ "4 False ... \n",
+ "\n",
+ " FACTS CAUSING DISENGAGEMENT_precautionary takeover to address planning, \\nprecautionary takeover to address perception, \\nother road user behaving poorly \\\n",
+ "0 False \n",
+ "1 False \n",
+ "2 False \n",
+ "3 False \n",
+ "4 False \n",
+ "\n",
+ " FACTS CAUSING DISENGAGEMENT_precautionary takeover to address planning, \\nprecautionary takeover to address perception, AV made unsuccessful left turn \\\n",
+ "0 False \n",
+ "1 False \n",
+ "2 False \n",
+ "3 False \n",
+ "4 False \n",
+ "\n",
+ " FACTS CAUSING DISENGAGEMENT_precautionary takeover to address planning, \\nprecautionary takeover to address perception, third party lane encroachment \\\n",
+ "0 False \n",
+ "1 False \n",
+ "2 False \n",
+ "3 False \n",
+ "4 False \n",
+ "\n",
+ " FACTS CAUSING DISENGAGEMENT_precautionary takeover to address planning, \\nprecautionary takeover to address perception, third party lane obstruction \\\n",
+ "0 False \n",
+ "1 False \n",
+ "2 False \n",
+ "3 False \n",
+ "4 False \n",
+ "\n",
+ " FACTS CAUSING DISENGAGEMENT_precautionary takeover to address planning, AV lane change issues \\\n",
+ "0 False \n",
+ "1 False \n",
+ "2 False \n",
+ "3 False \n",
+ "4 False \n",
+ "\n",
+ " FACTS CAUSING DISENGAGEMENT_precautionary takeover to address planning, AV made unsuccessful left turn \\\n",
+ "0 False \n",
+ "1 False \n",
+ "2 False \n",
+ "3 False \n",
+ "4 False \n",
+ "\n",
+ " FACTS CAUSING DISENGAGEMENT_precautionary takeover to address planning, other road user behaving poorly \\\n",
+ "0 False \n",
+ "1 False \n",
+ "2 False \n",
+ "3 False \n",
+ "4 False \n",
+ "\n",
+ " FACTS CAUSING DISENGAGEMENT_precautionary takeover to address planning, third party lane encroachment \\\n",
+ "0 False \n",
+ "1 False \n",
+ "2 False \n",
+ "3 False \n",
+ "4 False \n",
+ "\n",
+ " FACTS CAUSING DISENGAGEMENT_precautionary takeover to address planning, third party lane obstruction \\\n",
+ "0 False \n",
+ "1 False \n",
+ "2 False \n",
+ "3 False \n",
+ "4 False \n",
+ "\n",
+ " FACTS CAUSING DISENGAGEMENT_prediction discrepancy, a vehicle in the front was backing up, ego was not able to predict this behavior correctly. \n",
+ "0 False \n",
+ "1 False \n",
+ "2 False \n",
+ "3 False \n",
+ "4 False \n",
+ "\n",
+ "[5 rows x 4538 columns]"
+ ]
+ },
+ "execution_count": 116,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "data_with_dummies = pd.get_dummies(data_preprocessed, drop_first=True)\n",
+ "data_with_dummies.head()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 117,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "Problem class 0\n",
+ "Manufacturer_Apple Inc. 0\n",
+ "Manufacturer_Aurora Innovation, Inc. 0\n",
+ "Manufacturer_AutoX Technologies, Inc. 0\n",
+ "Manufacturer_BMW of North America 0\n",
+ " ..\n",
+ "FACTS CAUSING DISENGAGEMENT_precautionary takeover to address planning, AV made unsuccessful left turn 0\n",
+ "FACTS CAUSING DISENGAGEMENT_precautionary takeover to address planning, other road user behaving poorly 0\n",
+ "FACTS CAUSING DISENGAGEMENT_precautionary takeover to address planning, third party lane encroachment 0\n",
+ "FACTS CAUSING DISENGAGEMENT_precautionary takeover to address planning, third party lane obstruction 0\n",
+ "FACTS CAUSING DISENGAGEMENT_prediction discrepancy, a vehicle in the front was backing up, ego was not able to predict this behavior correctly. 0\n",
+ "Length: 4538, dtype: int64"
+ ]
+ },
+ "execution_count": 117,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "data_with_dummies.isnull().sum()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 118,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from sklearn.model_selection import train_test_split\n",
+ "from sklearn.metrics import confusion_matrix, accuracy_score, classification_report"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 119,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "target = data_with_dummies['Problem class']\n",
+ "inputs = data_with_dummies.drop(['Problem class'],axis=1)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 120,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "x_train, x_test, y_train, y_test = train_test_split(inputs, target, test_size=0.2, random_state=365)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 121,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "C:\\Users\\ar\\AppData\\Local\\Temp\\ipykernel_3376\\2234393116.py:1: UserWarning: \n",
+ "\n",
+ "`distplot` is a deprecated function and will be removed in seaborn v0.14.0.\n",
+ "\n",
+ "Please adapt your code to use either `displot` (a figure-level function with\n",
+ "similar flexibility) or `histplot` (an axes-level function for histograms).\n",
+ "\n",
+ "For a guide to updating your code to use the new functions, please see\n",
+ "https://gist.github.com/mwaskom/de44147ed2974457ad6372750bbe5751\n",
+ "\n",
+ " sns.distplot((y_test),bins=50)\n"
+ ]
+ },
+ {
+ "data": {
+ "text/plain": [
+ "<Axes: xlabel='Problem class', ylabel='Density'>"
+ ]
+ },
+ "execution_count": 121,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "<Figure size 640x480 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "sns.distplot((y_test),bins=50)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Decision Tree"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 124,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from sklearn.tree import DecisionTreeClassifier"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 125,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "dtree = DecisionTreeClassifier()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 126,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
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+ ],
+ "text/plain": [
+ "DecisionTreeClassifier()"
+ ]
+ },
+ "execution_count": 126,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "dtree.fit(x_train,y_train)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 127,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "predictions = dtree.predict(x_test)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 128,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ " precision recall f1-score support\n",
+ "\n",
+ " 0 0.99 0.99 0.99 531\n",
+ " 1 1.00 0.94 0.97 17\n",
+ " 2 0.99 0.98 0.98 527\n",
+ " 3 0.00 0.00 0.00 1\n",
+ " 4 0.79 0.96 0.87 24\n",
+ " 5 1.00 0.80 0.89 10\n",
+ " 6 0.99 0.99 0.99 667\n",
+ "\n",
+ " accuracy 0.99 1777\n",
+ " macro avg 0.82 0.81 0.81 1777\n",
+ "weighted avg 0.99 0.99 0.99 1777\n",
+ "\n"
+ ]
+ }
+ ],
+ "source": [
+ "print(classification_report(y_test,predictions))"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3 (ipykernel)",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.11.5"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}