accuracy_LR.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "accuracy_LR.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/gandalf1819/SF-Opioid-Crisis/blob/master/accuracy_LR.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "z4U727EIDj2V",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt \n",
        "import seaborn as sns\n",
        "from sklearn.metrics import accuracy_score\n",
        "from sklearn.metrics import roc_curve, roc_auc_score\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.linear_model import LogisticRegression\n",
        "from math import ceil\n",
        "import scipy.stats as stats \n",
        "from sklearn.metrics import precision_recall_fscore_support, confusion_matrix\n",
        "%matplotlib inline"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "r6ftwYUIDj4u",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "d_crime = pd.read_csv(\"/content/gdrive/My Drive/SF dataset/Police_Department_Incident_Reports__Historical_2003_to_May_2018.csv\")"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-9r1DHknDj7N",
        "colab_type": "code",
        "outputId": "319e4eb1-a200-4bb0-f67d-db8974c38102",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 253
        }
      },
      "source": [
        "d_crime.head(2)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>IncidntNum</th>\n",
              "      <th>Category</th>\n",
              "      <th>Descript</th>\n",
              "      <th>DayOfWeek</th>\n",
              "      <th>Date</th>\n",
              "      <th>Time</th>\n",
              "      <th>PdDistrict</th>\n",
              "      <th>Resolution</th>\n",
              "      <th>Address</th>\n",
              "      <th>X</th>\n",
              "      <th>Y</th>\n",
              "      <th>Location</th>\n",
              "      <th>PdId</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>146196161</td>\n",
              "      <td>NON-CRIMINAL</td>\n",
              "      <td>LOST PROPERTY</td>\n",
              "      <td>Tuesday</td>\n",
              "      <td>09/23/2014</td>\n",
              "      <td>01:00</td>\n",
              "      <td>SOUTHERN</td>\n",
              "      <td>NONE</td>\n",
              "      <td>800 Block of BRYANT ST</td>\n",
              "      <td>-122.403405</td>\n",
              "      <td>37.775421</td>\n",
              "      <td>POINT (-122.403404791479 37.775420706711)</td>\n",
              "      <td>14619616171000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>150045675</td>\n",
              "      <td>ASSAULT</td>\n",
              "      <td>BATTERY</td>\n",
              "      <td>Thursday</td>\n",
              "      <td>01/15/2015</td>\n",
              "      <td>17:00</td>\n",
              "      <td>TARAVAL</td>\n",
              "      <td>NONE</td>\n",
              "      <td>1800 Block of VICENTE ST</td>\n",
              "      <td>-122.485604</td>\n",
              "      <td>37.738821</td>\n",
              "      <td>POINT (-122.48560378101 37.7388214326705)</td>\n",
              "      <td>15004567504134</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   IncidntNum  ...            PdId\n",
              "0   146196161  ...  14619616171000\n",
              "1   150045675  ...  15004567504134\n",
              "\n",
              "[2 rows x 13 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZblzZA3jDj9x",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "#setting x variable and y variable\n",
        "x = [\"X\",\"Y\",\"PdDistrict\"]\n",
        "y = \"Category\""
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "u7yHt5OLDkAd",
        "colab_type": "code",
        "outputId": "92d69fc7-7f4b-4ca7-e16d-dec93ec6bcc2",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 918
        }
      },
      "source": [
        "#This function transforms the categorical y into numeric, and prepare it for multiclass classfication\n",
        "def transformation(dataset,y,x):\n",
        "  for i in dataset.columns:\n",
        "    if i not in x and i != y:\n",
        "      dataset.drop(i,axis=1,inplace=True)         #drop unrelavent columns\n",
        "  dataset.dropna(axis=0, how='any', inplace=True)    \n",
        "  neighborhood=pd.get_dummies(dataset[\"PdDistrict\"])\n",
        "  dataset=pd.concat([dataset,neighborhood],axis=1)\n",
        "  dataset.drop(\"PdDistrict\",axis=1,inplace=True)\n",
        "  y_variable = dataset[y].unique()\n",
        "  dic_y = {}                       # use a dictionary to temporarily hold crime data, transform crime into numeric representation\n",
        "  i = 1 \n",
        "  for crime_type in y_variable:         \n",
        "    dic_y[crime_type]=i\n",
        "    i=i+1\n",
        "  dataset.replace(to_replace=dic_y,inplace=True)\n",
        "  return dataset,dic_y\n",
        "\n",
        "df,temp = transformation(d_crime,y,x)\n",
        "df,temp"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(         Category           X          Y  ...  SOUTHERN  TARAVAL  TENDERLOIN\n",
              " 0               1 -122.403405  37.775421  ...         1        0           0\n",
              " 1               2 -122.485604  37.738821  ...         0        1           0\n",
              " 2               3 -122.396535  37.710660  ...         0        0           0\n",
              " 3               2 -122.400131  37.730093  ...         0        0           0\n",
              " 4               4 -120.500000  90.000000  ...         0        0           0\n",
              " ...           ...         ...        ...  ...       ...      ...         ...\n",
              " 2215019         1 -122.414406  37.775236  ...         1        0           0\n",
              " 2215020         4 -122.389103  37.766904  ...         0        0           0\n",
              " 2215021         6 -122.436214  37.771317  ...         0        0           0\n",
              " 2215022        31 -122.434155  37.802896  ...         0        0           0\n",
              " 2215023         4 -122.424702  37.735370  ...         0        0           0\n",
              " \n",
              " [2215023 rows x 13 columns],\n",
              " {'ARSON': 7,\n",
              "  'ASSAULT': 2,\n",
              "  'BAD CHECKS': 32,\n",
              "  'BRIBERY': 34,\n",
              "  'BURGLARY': 12,\n",
              "  'DISORDERLY CONDUCT': 20,\n",
              "  'DRIVING UNDER THE INFLUENCE': 28,\n",
              "  'DRUG/NARCOTIC': 14,\n",
              "  'DRUNKENNESS': 22,\n",
              "  'EMBEZZLEMENT': 24,\n",
              "  'EXTORTION': 39,\n",
              "  'FAMILY OFFENSES': 21,\n",
              "  'FORGERY/COUNTERFEITING': 18,\n",
              "  'FRAUD': 8,\n",
              "  'GAMBLING': 33,\n",
              "  'KIDNAPPING': 17,\n",
              "  'LARCENY/THEFT': 10,\n",
              "  'LIQUOR LAWS': 29,\n",
              "  'LOITERING': 31,\n",
              "  'MISSING PERSON': 11,\n",
              "  'NON-CRIMINAL': 1,\n",
              "  'OTHER OFFENSES': 4,\n",
              "  'PORNOGRAPHY/OBSCENE MAT': 38,\n",
              "  'PROSTITUTION': 36,\n",
              "  'RECOVERED VEHICLE': 26,\n",
              "  'ROBBERY': 16,\n",
              "  'RUNAWAY': 35,\n",
              "  'SECONDARY CODES': 9,\n",
              "  'SEX OFFENSES, FORCIBLE': 25,\n",
              "  'SEX OFFENSES, NON FORCIBLE': 37,\n",
              "  'STOLEN PROPERTY': 27,\n",
              "  'SUICIDE': 5,\n",
              "  'SUSPICIOUS OCC': 3,\n",
              "  'TREA': 30,\n",
              "  'TRESPASS': 19,\n",
              "  'VANDALISM': 15,\n",
              "  'VEHICLE THEFT': 6,\n",
              "  'WARRANTS': 13,\n",
              "  'WEAPON LAWS': 23})"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DaECa1TDDkDR",
        "colab_type": "code",
        "outputId": "dc2f06cf-0a00-49ad-c685-422db7fbe7b0",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 298
        }
      },
      "source": [
        "sns.countplot(x=\"Category\",data=df)  #shows the number of crimes in numeric representation"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f50a8e8ec18>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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292HA3fEe4AhgWLzGAtdAChjABcCBwAHABYWgcQ3w8cLnRqyjDRERabFsd5e5+y/MbGgp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\nEJTiwaz2AAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jm6bHBwtDkF8",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# I dropped Y variable for X, and split dataset 0.3 vs 0.7\n",
        "X=df.drop(\"Category\",axis=1)\n",
        "Y=df[\"Category\"]\n",
        "x_train,x_test,y_train,y_test = train_test_split(X,Y,test_size=0.3)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4BVT8T4GDkI6",
        "colab_type": "code",
        "outputId": "aaa8e2f0-329c-4621-fad2-c959317f79c7",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 165
        }
      },
      "source": [
        "#build a multinomial logistic model\n",
        "log_model = LogisticRegression().fit(x_train,y_train)\n",
        "prediction = log_model.predict(x_test)\n",
        "prediction"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/logistic.py:432: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
            "  FutureWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/logistic.py:469: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
            "  \"this warning.\", FutureWarning)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([10,  4, 10, ..., 14, 10, 10])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tusJt4dVDkLr",
        "colab_type": "code",
        "outputId": "1f0f1418-5bfe-48de-d0ba-b1786318b5dc",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "#Evaluate the model based on prediction accuracy\n",
        "model_score = accuracy_score(y_test,prediction)\n",
        "print(\"accuracy score is: \"+str(model_score))"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "accuracy score is: 0.42857142857142855\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ey7vUG4DDkOW",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "#predict the log-probability of the sample for each class/crime\n",
        "proba = log_model.predict_proba(x_test)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "U1KPDC95D3UU",
        "colab_type": "text"
      },
      "source": [
        "this table shows the likelihood of each crime happening on that geo cordinates"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EeW42HcKDkQu",
        "colab_type": "code",
        "outputId": "4612ef7f-6721-40e2-ac24-ec09ca281a78",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 490
        }
      },
      "source": [
        "#this function takes as input a dictionary, and return the key\n",
        "def getback_columns(dictionary,number):\n",
        "  for key,value in dictionary.items():\n",
        "      if value==number:\n",
        "        return key\n",
        "      else:\n",
        "        continue\n",
        "column_names = []       # this list holds column names so will be used later to construct the output table\n",
        "for classes in log_model.classes_:\n",
        "  key = getback_columns(temp,classes)\n",
        "  column_names.append(key)\n",
        "column_names\n",
        "output_table = pd.DataFrame(proba, columns=column_names)\n",
        "output_table"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>NON-CRIMINAL</th>\n",
              "      <th>ASSAULT</th>\n",
              "      <th>SUSPICIOUS OCC</th>\n",
              "      <th>OTHER OFFENSES</th>\n",
              "      <th>SUICIDE</th>\n",
              "      <th>VEHICLE THEFT</th>\n",
              "      <th>ARSON</th>\n",
              "      <th>FRAUD</th>\n",
              "      <th>SECONDARY CODES</th>\n",
              "      <th>LARCENY/THEFT</th>\n",
              "      <th>MISSING PERSON</th>\n",
              "      <th>BURGLARY</th>\n",
              "      <th>WARRANTS</th>\n",
              "      <th>DRUG/NARCOTIC</th>\n",
              "      <th>VANDALISM</th>\n",
              "      <th>ROBBERY</th>\n",
              "      <th>KIDNAPPING</th>\n",
              "      <th>FORGERY/COUNTERFEITING</th>\n",
              "      <th>TRESPASS</th>\n",
              "      <th>DISORDERLY CONDUCT</th>\n",
              "      <th>FAMILY OFFENSES</th>\n",
              "      <th>DRUNKENNESS</th>\n",
              "      <th>WEAPON LAWS</th>\n",
              "      <th>EMBEZZLEMENT</th>\n",
              "      <th>SEX OFFENSES, FORCIBLE</th>\n",
              "      <th>RECOVERED VEHICLE</th>\n",
              "      <th>STOLEN PROPERTY</th>\n",
              "      <th>DRIVING UNDER THE INFLUENCE</th>\n",
              "      <th>LIQUOR LAWS</th>\n",
              "      <th>TREA</th>\n",
              "      <th>LOITERING</th>\n",
              "      <th>BAD CHECKS</th>\n",
              "      <th>GAMBLING</th>\n",
              "      <th>BRIBERY</th>\n",
              "      <th>RUNAWAY</th>\n",
              "      <th>PROSTITUTION</th>\n",
              "      <th>SEX OFFENSES, NON FORCIBLE</th>\n",
              "      <th>PORNOGRAPHY/OBSCENE MAT</th>\n",
              "      <th>EXTORTION</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0.125662</td>\n",
              "      <td>0.077383</td>\n",
              "      <td>0.033189</td>\n",
              "      <td>0.101023</td>\n",
              "      <td>0.000632</td>\n",
              "      <td>0.044714</td>\n",
              "      <td>0.001267</td>\n",
              "      <td>0.026116</td>\n",
              "      <td>0.008407</td>\n",
              "      <td>0.317843</td>\n",
              "      <td>0.017887</td>\n",
              "      <td>0.048995</td>\n",
              "      <td>0.030537</td>\n",
              "      <td>0.017902</td>\n",
              "      <td>0.055412</td>\n",
              "      <td>0.023076</td>\n",
              "      <td>0.001859</td>\n",
              "      <td>0.011502</td>\n",
              "      <td>0.010939</td>\n",
              "      <td>0.004461</td>\n",
              "      <td>0.000258</td>\n",
              "      <td>0.005356</td>\n",
              "      <td>0.005772</td>\n",
              "      <td>0.002084</td>\n",
              "      <td>0.004662</td>\n",
              "      <td>0.002490</td>\n",
              "      <td>0.006329</td>\n",
              "      <td>0.001776</td>\n",
              "      <td>0.001248</td>\n",
              "      <td>0.000006</td>\n",
              "      <td>0.000688</td>\n",
              "      <td>0.000566</td>\n",
              "      <td>0.000260</td>\n",
              "      <td>0.000201</td>\n",
              "      <td>0.000523</td>\n",
              "      <td>0.008258</td>\n",
              "      <td>0.000064</td>\n",
              "      <td>0.000021</td>\n",
              "      <td>0.000632</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.073673</td>\n",
              "      <td>0.113586</td>\n",
              "      <td>0.044192</td>\n",
              "      <td>0.185786</td>\n",
              "      <td>0.000368</td>\n",
              "      <td>0.077939</td>\n",
              "      <td>0.004526</td>\n",
              "      <td>0.010320</td>\n",
              "      <td>0.019328</td>\n",
              "      <td>0.126773</td>\n",
              "      <td>0.039421</td>\n",
              "      <td>0.043931</td>\n",
              "      <td>0.047310</td>\n",
              "      <td>0.045893</td>\n",
              "      <td>0.064239</td>\n",
              "      <td>0.029623</td>\n",
              "      <td>0.003745</td>\n",
              "      <td>0.007724</td>\n",
              "      <td>0.007760</td>\n",
              "      <td>0.002455</td>\n",
              "      <td>0.000776</td>\n",
              "      <td>0.002634</td>\n",
              "      <td>0.019632</td>\n",
              "      <td>0.001421</td>\n",
              "      <td>0.004634</td>\n",
              "      <td>0.009186</td>\n",
              "      <td>0.004364</td>\n",
              "      <td>0.002114</td>\n",
              "      <td>0.001230</td>\n",
              "      <td>0.000014</td>\n",
              "      <td>0.000462</td>\n",
              "      <td>0.000333</td>\n",
              "      <td>0.000261</td>\n",
              "      <td>0.000674</td>\n",
              "      <td>0.002460</td>\n",
              "      <td>0.000706</td>\n",
              "      <td>0.000232</td>\n",
              "      <td>0.000032</td>\n",
              "      <td>0.000242</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.109997</td>\n",
              "      <td>0.081272</td>\n",
              "      <td>0.044748</td>\n",
              "      <td>0.134396</td>\n",
              "      <td>0.000914</td>\n",
              "      <td>0.082985</td>\n",
              "      <td>0.002136</td>\n",
              "      <td>0.023659</td>\n",
              "      <td>0.017334</td>\n",
              "      <td>0.193083</td>\n",
              "      <td>0.053082</td>\n",
              "      <td>0.052438</td>\n",
              "      <td>0.024082</td>\n",
              "      <td>0.020477</td>\n",
              "      <td>0.068788</td>\n",
              "      <td>0.020097</td>\n",
              "      <td>0.002593</td>\n",
              "      <td>0.014226</td>\n",
              "      <td>0.006632</td>\n",
              "      <td>0.002109</td>\n",
              "      <td>0.000560</td>\n",
              "      <td>0.003940</td>\n",
              "      <td>0.008418</td>\n",
              "      <td>0.001554</td>\n",
              "      <td>0.005890</td>\n",
              "      <td>0.004177</td>\n",
              "      <td>0.004099</td>\n",
              "      <td>0.003385</td>\n",
              "      <td>0.001626</td>\n",
              "      <td>0.000012</td>\n",
              "      <td>0.000446</td>\n",
              "      <td>0.000600</td>\n",
              "      <td>0.000114</td>\n",
              "      <td>0.000298</td>\n",
              "      <td>0.006263</td>\n",
              "      <td>0.002435</td>\n",
              "      <td>0.000413</td>\n",
              "      <td>0.000033</td>\n",
              "      <td>0.000691</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.125956</td>\n",
              "      <td>0.077575</td>\n",
              "      <td>0.033273</td>\n",
              "      <td>0.101293</td>\n",
              "      <td>0.000633</td>\n",
              "      <td>0.044840</td>\n",
              "      <td>0.001268</td>\n",
              "      <td>0.026184</td>\n",
              "      <td>0.008416</td>\n",
              "      <td>0.318653</td>\n",
              "      <td>0.015489</td>\n",
              "      <td>0.049103</td>\n",
              "      <td>0.030617</td>\n",
              "      <td>0.017945</td>\n",
              "      <td>0.055526</td>\n",
              "      <td>0.023135</td>\n",
              "      <td>0.001865</td>\n",
              "      <td>0.011524</td>\n",
              "      <td>0.010967</td>\n",
              "      <td>0.004471</td>\n",
              "      <td>0.000258</td>\n",
              "      <td>0.005368</td>\n",
              "      <td>0.005780</td>\n",
              "      <td>0.002088</td>\n",
              "      <td>0.004675</td>\n",
              "      <td>0.002492</td>\n",
              "      <td>0.006347</td>\n",
              "      <td>0.001779</td>\n",
              "      <td>0.001251</td>\n",
              "      <td>0.000006</td>\n",
              "      <td>0.000690</td>\n",
              "      <td>0.000567</td>\n",
              "      <td>0.000260</td>\n",
              "      <td>0.000201</td>\n",
              "      <td>0.000506</td>\n",
              "      <td>0.008281</td>\n",
              "      <td>0.000064</td>\n",
              "      <td>0.000021</td>\n",
              "      <td>0.000633</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0.073314</td>\n",
              "      <td>0.113020</td>\n",
              "      <td>0.043969</td>\n",
              "      <td>0.184834</td>\n",
              "      <td>0.000366</td>\n",
              "      <td>0.077528</td>\n",
              "      <td>0.004510</td>\n",
              "      <td>0.010268</td>\n",
              "      <td>0.019252</td>\n",
              "      <td>0.126133</td>\n",
              "      <td>0.044107</td>\n",
              "      <td>0.043722</td>\n",
              "      <td>0.047069</td>\n",
              "      <td>0.045665</td>\n",
              "      <td>0.063940</td>\n",
              "      <td>0.029473</td>\n",
              "      <td>0.003725</td>\n",
              "      <td>0.007688</td>\n",
              "      <td>0.007720</td>\n",
              "      <td>0.002443</td>\n",
              "      <td>0.000773</td>\n",
              "      <td>0.002621</td>\n",
              "      <td>0.019552</td>\n",
              "      <td>0.001414</td>\n",
              "      <td>0.004610</td>\n",
              "      <td>0.009151</td>\n",
              "      <td>0.004341</td>\n",
              "      <td>0.002105</td>\n",
              "      <td>0.001224</td>\n",
              "      <td>0.000014</td>\n",
              "      <td>0.000460</td>\n",
              "      <td>0.000331</td>\n",
              "      <td>0.000260</td>\n",
              "      <td>0.000671</td>\n",
              "      <td>0.002519</td>\n",
              "      <td>0.000702</td>\n",
              "      <td>0.000231</td>\n",
              "      <td>0.000032</td>\n",
              "      <td>0.000241</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>664502</th>\n",
              "      <td>0.091721</td>\n",
              "      <td>0.113224</td>\n",
              "      <td>0.040438</td>\n",
              "      <td>0.168346</td>\n",
              "      <td>0.000800</td>\n",
              "      <td>0.104854</td>\n",
              "      <td>0.002414</td>\n",
              "      <td>0.015213</td>\n",
              "      <td>0.017826</td>\n",
              "      <td>0.132714</td>\n",
              "      <td>0.043056</td>\n",
              "      <td>0.041883</td>\n",
              "      <td>0.031016</td>\n",
              "      <td>0.026512</td>\n",
              "      <td>0.067397</td>\n",
              "      <td>0.032944</td>\n",
              "      <td>0.003918</td>\n",
              "      <td>0.010905</td>\n",
              "      <td>0.005156</td>\n",
              "      <td>0.001978</td>\n",
              "      <td>0.000850</td>\n",
              "      <td>0.002426</td>\n",
              "      <td>0.014823</td>\n",
              "      <td>0.000883</td>\n",
              "      <td>0.006925</td>\n",
              "      <td>0.008407</td>\n",
              "      <td>0.004716</td>\n",
              "      <td>0.002699</td>\n",
              "      <td>0.001120</td>\n",
              "      <td>0.000007</td>\n",
              "      <td>0.000272</td>\n",
              "      <td>0.000417</td>\n",
              "      <td>0.000293</td>\n",
              "      <td>0.000757</td>\n",
              "      <td>0.001848</td>\n",
              "      <td>0.000416</td>\n",
              "      <td>0.000371</td>\n",
              "      <td>0.000029</td>\n",
              "      <td>0.000425</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>664503</th>\n",
              "      <td>0.097390</td>\n",
              "      <td>0.076687</td>\n",
              "      <td>0.031075</td>\n",
              "      <td>0.113301</td>\n",
              "      <td>0.000638</td>\n",
              "      <td>0.054705</td>\n",
              "      <td>0.001446</td>\n",
              "      <td>0.019742</td>\n",
              "      <td>0.009218</td>\n",
              "      <td>0.296058</td>\n",
              "      <td>0.018255</td>\n",
              "      <td>0.052875</td>\n",
              "      <td>0.040752</td>\n",
              "      <td>0.039659</td>\n",
              "      <td>0.053246</td>\n",
              "      <td>0.023657</td>\n",
              "      <td>0.001875</td>\n",
              "      <td>0.010228</td>\n",
              "      <td>0.007933</td>\n",
              "      <td>0.004164</td>\n",
              "      <td>0.000234</td>\n",
              "      <td>0.002972</td>\n",
              "      <td>0.007456</td>\n",
              "      <td>0.001228</td>\n",
              "      <td>0.004448</td>\n",
              "      <td>0.002910</td>\n",
              "      <td>0.006705</td>\n",
              "      <td>0.002178</td>\n",
              "      <td>0.001011</td>\n",
              "      <td>0.000006</td>\n",
              "      <td>0.001422</td>\n",
              "      <td>0.000522</td>\n",
              "      <td>0.000068</td>\n",
              "      <td>0.000215</td>\n",
              "      <td>0.000727</td>\n",
              "      <td>0.014627</td>\n",
              "      <td>0.000102</td>\n",
              "      <td>0.000022</td>\n",
              "      <td>0.000242</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>664504</th>\n",
              "      <td>0.096755</td>\n",
              "      <td>0.098361</td>\n",
              "      <td>0.033490</td>\n",
              "      <td>0.159030</td>\n",
              "      <td>0.000464</td>\n",
              "      <td>0.013381</td>\n",
              "      <td>0.000953</td>\n",
              "      <td>0.013816</td>\n",
              "      <td>0.009155</td>\n",
              "      <td>0.130560</td>\n",
              "      <td>0.011777</td>\n",
              "      <td>0.019158</td>\n",
              "      <td>0.085157</td>\n",
              "      <td>0.199806</td>\n",
              "      <td>0.022790</td>\n",
              "      <td>0.027588</td>\n",
              "      <td>0.002701</td>\n",
              "      <td>0.006619</td>\n",
              "      <td>0.014068</td>\n",
              "      <td>0.009477</td>\n",
              "      <td>0.000352</td>\n",
              "      <td>0.005097</td>\n",
              "      <td>0.010382</td>\n",
              "      <td>0.001383</td>\n",
              "      <td>0.004164</td>\n",
              "      <td>0.002393</td>\n",
              "      <td>0.004395</td>\n",
              "      <td>0.001383</td>\n",
              "      <td>0.002330</td>\n",
              "      <td>0.000004</td>\n",
              "      <td>0.001880</td>\n",
              "      <td>0.000225</td>\n",
              "      <td>0.000161</td>\n",
              "      <td>0.000229</td>\n",
              "      <td>0.000141</td>\n",
              "      <td>0.010101</td>\n",
              "      <td>0.000093</td>\n",
              "      <td>0.000035</td>\n",
              "      <td>0.000148</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>664505</th>\n",
              "      <td>0.097154</td>\n",
              "      <td>0.076489</td>\n",
              "      <td>0.030991</td>\n",
              "      <td>0.112995</td>\n",
              "      <td>0.000637</td>\n",
              "      <td>0.054544</td>\n",
              "      <td>0.001444</td>\n",
              "      <td>0.019686</td>\n",
              "      <td>0.009203</td>\n",
              "      <td>0.295309</td>\n",
              "      <td>0.020764</td>\n",
              "      <td>0.052748</td>\n",
              "      <td>0.040639</td>\n",
              "      <td>0.039554</td>\n",
              "      <td>0.053126</td>\n",
              "      <td>0.023591</td>\n",
              "      <td>0.001869</td>\n",
              "      <td>0.010204</td>\n",
              "      <td>0.007910</td>\n",
              "      <td>0.004153</td>\n",
              "      <td>0.000234</td>\n",
              "      <td>0.002964</td>\n",
              "      <td>0.007443</td>\n",
              "      <td>0.001225</td>\n",
              "      <td>0.004434</td>\n",
              "      <td>0.002905</td>\n",
              "      <td>0.006683</td>\n",
              "      <td>0.002173</td>\n",
              "      <td>0.001009</td>\n",
              "      <td>0.000006</td>\n",
              "      <td>0.001418</td>\n",
              "      <td>0.000521</td>\n",
              "      <td>0.000067</td>\n",
              "      <td>0.000215</td>\n",
              "      <td>0.000748</td>\n",
              "      <td>0.014579</td>\n",
              "      <td>0.000102</td>\n",
              "      <td>0.000022</td>\n",
              "      <td>0.000242</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>664506</th>\n",
              "      <td>0.125940</td>\n",
              "      <td>0.077568</td>\n",
              "      <td>0.033275</td>\n",
              "      <td>0.101276</td>\n",
              "      <td>0.000633</td>\n",
              "      <td>0.044839</td>\n",
              "      <td>0.001268</td>\n",
              "      <td>0.026187</td>\n",
              "      <td>0.008419</td>\n",
              "      <td>0.318572</td>\n",
              "      <td>0.015572</td>\n",
              "      <td>0.049104</td>\n",
              "      <td>0.030618</td>\n",
              "      <td>0.017946</td>\n",
              "      <td>0.055526</td>\n",
              "      <td>0.023138</td>\n",
              "      <td>0.001866</td>\n",
              "      <td>0.011527</td>\n",
              "      <td>0.010970</td>\n",
              "      <td>0.004473</td>\n",
              "      <td>0.000258</td>\n",
              "      <td>0.005369</td>\n",
              "      <td>0.005781</td>\n",
              "      <td>0.002090</td>\n",
              "      <td>0.004676</td>\n",
              "      <td>0.002493</td>\n",
              "      <td>0.006349</td>\n",
              "      <td>0.001780</td>\n",
              "      <td>0.001251</td>\n",
              "      <td>0.000006</td>\n",
              "      <td>0.000690</td>\n",
              "      <td>0.000567</td>\n",
              "      <td>0.000261</td>\n",
              "      <td>0.000201</td>\n",
              "      <td>0.000507</td>\n",
              "      <td>0.008284</td>\n",
              "      <td>0.000064</td>\n",
              "      <td>0.000021</td>\n",
              "      <td>0.000634</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>664507 rows × 39 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "        NON-CRIMINAL   ASSAULT  ...  PORNOGRAPHY/OBSCENE MAT  EXTORTION\n",
              "0           0.125662  0.077383  ...                 0.000021   0.000632\n",
              "1           0.073673  0.113586  ...                 0.000032   0.000242\n",
              "2           0.109997  0.081272  ...                 0.000033   0.000691\n",
              "3           0.125956  0.077575  ...                 0.000021   0.000633\n",
              "4           0.073314  0.113020  ...                 0.000032   0.000241\n",
              "...              ...       ...  ...                      ...        ...\n",
              "664502      0.091721  0.113224  ...                 0.000029   0.000425\n",
              "664503      0.097390  0.076687  ...                 0.000022   0.000242\n",
              "664504      0.096755  0.098361  ...                 0.000035   0.000148\n",
              "664505      0.097154  0.076489  ...                 0.000022   0.000242\n",
              "664506      0.125940  0.077568  ...                 0.000021   0.000634\n",
              "\n",
              "[664507 rows x 39 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rIDcU8cXD08q",
        "colab_type": "code",
        "outputId": "be9f35dc-579d-4991-fddd-2bd28cb6622f",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 68
        }
      },
      "source": [
        "#Evaluating the model with precision, recall, and f1 score\n",
        "storage = precision_recall_fscore_support(y_test,prediction,average=\"weighted\")\n",
        "precision = storage[0]\n",
        "recall = storage[1]\n",
        "fscore = storage[2]\n",
        "print(\"precision is %.2f\" %precision)\n",
        "print(\"recall is %.2f\" %recall)\n",
        "print(\"fscore is %.2f\" %fscore)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "precision is 0.33\n",
            "recall is 0.43\n",
            "fscore is 0.36\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZlM1hXjND07Y",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "#Evaluate the model with confusion matrix\n",
        "matrix = confusion_matrix(y_test,prediction )"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kQEbXSJ8D03E",
        "colab_type": "code",
        "outputId": "c2759e99-49ae-495c-dd67-1b56bf0aee08",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 776
        }
      },
      "source": [
        "#Put confusion matrix data into a dataframe, and visualize it with heatmap\n",
        "confusion_df = pd.DataFrame(matrix,\n",
        "                     index = temp.keys(), \n",
        "                     columns = temp.keys())\n",
        "plt.figure(figsize=(10,10))\n",
        "plt.title('Multinomial logistic regression\\nAccuracy:{0:.3f}'.format(model_score))\n",
        "plt.ylabel('True label')\n",
        "plt.xlabel('Predicted label')\n",
        "sns.heatmap(confusion_df, annot=True)\n",
        "plt.show()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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NEUtZunhmtvfJjjvvaM+pmF2cj99HVOQaKleumKY+MNCfuFO7efGFJ136zsxzSuyO7eGc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U2+Pim+Vu1WEhFxSMIj/pRqNZpKKZ/qTvWdHeUD68qmTb/d4ePcuQvy05yF4uldVo4fPykr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CLHh/4pnpwDnWqjaLO5IOoctuZdPOT9lF2YHoI7Ad8HvC6f7xuO6MJTNHOtpJMiBN+a79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\n/w+2AvAfR/FWDQAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 720x720 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    }
  ]
}