ALDA_Project_midway.ipynb

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  "metadata": {
    "kernelspec": {
      "display_name": "Python 3",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.8.8"
    },
    "colab": {
      "name": "ALDA_Project.ipynb",
      "provenance": [],
      "collapsed_sections": []
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "1pz21ArYDFe0"
      },
      "source": [
        "# **WildFire Cause Prediction**\n",
        "\n",
        "Team : \n",
        "\n",
        "Ganesh Thanu (gthanu)\n",
        "\n",
        "Arun Gaonkar (agaonka)\n",
        "\n",
        "Nikhil Patil (npatil)\n"
      ],
      "id": "1pz21ArYDFe0"
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "93575a8b"
      },
      "source": [
        "#importing necessary libraries\n",
        "import sqlite3\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sb\n",
        "import numpy as np\n",
        "from mpl_toolkits.mplot3d import Axes3D\n",
        "from sklearn.preprocessing import StandardScaler\n",
        "from sklearn import tree, preprocessing\n",
        "from sklearn.metrics import accuracy_score, plot_confusion_matrix, confusion_matrix, ConfusionMatrixDisplay,f1_score,precision_score,recall_score"
      ],
      "id": "93575a8b",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ALuYJmkemgrq",
        "outputId": "74ffb3c8-4371-4b43-d810-55a6e4f47139"
      },
      "source": [
        "#Mounting Google Drive\n",
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "id": "ALuYJmkemgrq",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jJq9DzDZjFcR",
        "outputId": "f88ffe76-1a59-4866-f3c4-d80f5284ebbe"
      },
      "source": [
        "cd '/content/drive/MyDrive/ALDA_Project'"
      ],
      "id": "jJq9DzDZjFcR",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/drive/MyDrive/ALDA_Project\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5Y_rtpddq9Zg"
      },
      "source": [
        "from sqlalchemy import create_engine\n",
        "my_conn=create_engine(\"sqlite:////content/drive/MyDrive/ALDA_Project/FPA_FOD_20170508.sqlite\")"
      ],
      "id": "5Y_rtpddq9Zg",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Vq3blnKvn_LT"
      },
      "source": [
        "# Reading the sql file \n",
        "df = pd.read_sql_query(\"SELECT FOD_ID, FIRE_YEAR, DISCOVERY_DATE, DISCOVERY_TIME, CONT_DATE, CONT_TIME, FIRE_SIZE, FIRE_SIZE_CLASS, LATITUDE, LONGITUDE, STATE, COUNTY, STAT_CAUSE_DESCR FROM Fires\", my_conn)\n",
        "df_original= df # a copy will be used later"
      ],
      "id": "Vq3blnKvn_LT",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "d4719597",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "f329d7fe-959d-4af3-ffeb-1d1f62c7e72e"
      },
      "source": [
        "#converting the data to normal datatime format\n",
        "df['START_DATE'] = pd.to_datetime(df['DISCOVERY_DATE'] - pd.Timestamp(0).to_julian_date(), unit='D')\n",
        "df['END_DATE'] = pd.to_datetime(df['CONT_DATE'] - pd.Timestamp(0).to_julian_date(), unit='D')\n",
        "df.drop(['DISCOVERY_DATE', 'CONT_DATE'], axis=1, inplace=True)\n",
        "df['MONTH'] = pd.DatetimeIndex(df['START_DATE']).month\n",
        "# Reordering the columns\n",
        "new_cols=['FOD_ID', 'FIRE_YEAR','MONTH','START_DATE','DISCOVERY_TIME', 'END_DATE','CONT_TIME', 'FIRE_SIZE', 'FIRE_SIZE_CLASS', 'LATITUDE', 'LONGITUDE', 'STATE', 'COUNTY', 'STAT_CAUSE_DESCR']\n",
        "df=df.reindex(columns=new_cols)\n",
        "\n",
        "# First five rows\n",
        "df.head()"
      ],
      "id": "d4719597",
      "execution_count": null,
      "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>FOD_ID</th>\n",
              "      <th>FIRE_YEAR</th>\n",
              "      <th>MONTH</th>\n",
              "      <th>START_DATE</th>\n",
              "      <th>DISCOVERY_TIME</th>\n",
              "      <th>END_DATE</th>\n",
              "      <th>CONT_TIME</th>\n",
              "      <th>FIRE_SIZE</th>\n",
              "      <th>FIRE_SIZE_CLASS</th>\n",
              "      <th>LATITUDE</th>\n",
              "      <th>LONGITUDE</th>\n",
              "      <th>STATE</th>\n",
              "      <th>COUNTY</th>\n",
              "      <th>STAT_CAUSE_DESCR</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>2005</td>\n",
              "      <td>2</td>\n",
              "      <td>2005-02-02</td>\n",
              "      <td>1300</td>\n",
              "      <td>2005-02-02</td>\n",
              "      <td>1730</td>\n",
              "      <td>0.10</td>\n",
              "      <td>A</td>\n",
              "      <td>40.036944</td>\n",
              "      <td>-121.005833</td>\n",
              "      <td>CA</td>\n",
              "      <td>63</td>\n",
              "      <td>Miscellaneous</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>2004</td>\n",
              "      <td>5</td>\n",
              "      <td>2004-05-12</td>\n",
              "      <td>0845</td>\n",
              "      <td>2004-05-12</td>\n",
              "      <td>1530</td>\n",
              "      <td>0.25</td>\n",
              "      <td>A</td>\n",
              "      <td>38.933056</td>\n",
              "      <td>-120.404444</td>\n",
              "      <td>CA</td>\n",
              "      <td>61</td>\n",
              "      <td>Lightning</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>2004</td>\n",
              "      <td>5</td>\n",
              "      <td>2004-05-31</td>\n",
              "      <td>1921</td>\n",
              "      <td>2004-05-31</td>\n",
              "      <td>2024</td>\n",
              "      <td>0.10</td>\n",
              "      <td>A</td>\n",
              "      <td>38.984167</td>\n",
              "      <td>-120.735556</td>\n",
              "      <td>CA</td>\n",
              "      <td>17</td>\n",
              "      <td>Debris Burning</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>2004</td>\n",
              "      <td>6</td>\n",
              "      <td>2004-06-28</td>\n",
              "      <td>1600</td>\n",
              "      <td>2004-07-03</td>\n",
              "      <td>1400</td>\n",
              "      <td>0.10</td>\n",
              "      <td>A</td>\n",
              "      <td>38.559167</td>\n",
              "      <td>-119.913333</td>\n",
              "      <td>CA</td>\n",
              "      <td>3</td>\n",
              "      <td>Lightning</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>2004</td>\n",
              "      <td>6</td>\n",
              "      <td>2004-06-28</td>\n",
              "      <td>1600</td>\n",
              "      <td>2004-07-03</td>\n",
              "      <td>1200</td>\n",
              "      <td>0.10</td>\n",
              "      <td>A</td>\n",
              "      <td>38.559167</td>\n",
              "      <td>-119.933056</td>\n",
              "      <td>CA</td>\n",
              "      <td>3</td>\n",
              "      <td>Lightning</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   FOD_ID  FIRE_YEAR  MONTH  ... STATE COUNTY STAT_CAUSE_DESCR\n",
              "0       1       2005      2  ...    CA     63    Miscellaneous\n",
              "1       2       2004      5  ...    CA     61        Lightning\n",
              "2       3       2004      5  ...    CA     17   Debris Burning\n",
              "3       4       2004      6  ...    CA      3        Lightning\n",
              "4       5       2004      6  ...    CA      3        Lightning\n",
              "\n",
              "[5 rows x 14 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3yuUVK-UaJ97",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "7882dc43-c9ca-4bf0-e7f6-331cae403a1e"
      },
      "source": [
        "df.shape"
      ],
      "id": "3yuUVK-UaJ97",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(1880465, 14)"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "CPBUbL2gsl42",
        "outputId": "d2177b22-ec8c-497b-8384-e6c2b5fa3def"
      },
      "source": [
        "#check mising values and columns\n",
        "df.columns[df.isnull().any()].tolist() "
      ],
      "id": "CPBUbL2gsl42",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['DISCOVERY_TIME', 'END_DATE', 'CONT_TIME', 'COUNTY']"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 281
        },
        "id": "79dVv_NZvGTe",
        "outputId": "7834dde0-bfcc-4f91-a35d-4d63e2e4cd2f"
      },
      "source": [
        "# Number of Fires and different reasons\n",
        "df['STAT_CAUSE_DESCR'].value_counts().plot(kind='barh')\n",
        "plt.title('WildFire Reasons and Count')\n",
        "plt.show()\n"
      ],
      "id": "79dVv_NZvGTe",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 411
        },
        "id": "Mo1KgK-OZqKe",
        "outputId": "02c29f96-94e6-4e26-bf86-188a52d49bf3"
      },
      "source": [
        "causes = df['STAT_CAUSE_DESCR'].value_counts()\n",
        "fig = plt.figure(figsize =(10, 7))\n",
        "plt.pie(causes, autopct='%1.1f%%',labels=causes.index)\n",
        "plt.show()"
      ],
      "id": "Mo1KgK-OZqKe",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x504 with 1 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "cnDbdeUbZxs7"
      },
      "source": [
        "Debris burning , Arson, Lightning are the major causes of wildfire accounting for more than 50% of total wildfires"
      ],
      "id": "cnDbdeUbZxs7"
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 265
        },
        "id": "oaU04JkmZ7ur",
        "outputId": "61e0fe46-7406-437b-f8f0-df3c0ef745b9"
      },
      "source": [
        "df['FIRE_YEAR'].value_counts().plot(kind='barh',color='lightblue')\n",
        "plt.show()"
      ],
      "id": "oaU04JkmZ7ur",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "WlEXM42yaBpm"
      },
      "source": [
        "There is no significant difference in year on year wildfire count"
      ],
      "id": "WlEXM42yaBpm"
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 411
        },
        "id": "EIUvNIb3aN16",
        "outputId": "0e0febc0-0044-4804-d501-e75ab50d2d51"
      },
      "source": [
        "months = df['MONTH'].value_counts()\n",
        "fig = plt.figure(figsize =(10, 7))\n",
        "plt.pie(months, autopct='%1.1f%%',labels=months.index)\n",
        "plt.show()"
      ],
      "id": "EIUvNIb3aN16",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x504 with 1 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Z4t9OyYEaWT8"
      },
      "source": [
        ""
      ],
      "id": "Z4t9OyYEaWT8",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kWCluJJXaSP8"
      },
      "source": [
        "There is significant difference between wildfire count from October-January and February-September. It might be because of weather, since weather is cold from October-January which is not conducive for wildfire. "
      ],
      "id": "kWCluJJXaSP8"
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 281
        },
        "id": "xKMI0Ej-vqKy",
        "outputId": "ce3c8ed1-5033-490b-93e0-6c1eecfa58f7"
      },
      "source": [
        "# Plotting statewise firecount\n",
        "df['STATE'].value_counts().head(n=10).plot(kind='barh')\n",
        "plt.title('StateWise fire count')\n",
        "plt.show()"
      ],
      "id": "xKMI0Ej-vqKy",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "eMoNXKDFalGf"
      },
      "source": [
        "df_CA = df[df['STATE']=='CA']\n",
        "df_GA = df[df['STATE']=='GA']\n",
        "df_TX = df[df['STATE']=='TX']"
      ],
      "id": "eMoNXKDFalGf",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 281
        },
        "id": "9VqgTUzqaoIo",
        "outputId": "bef8de53-88d5-49e8-95ad-1261f1832535"
      },
      "source": [
        "df_CA['STAT_CAUSE_DESCR'].value_counts().plot(kind='barh',color='lightblue',title='causes of fires for CA')\n",
        "plt.show()"
      ],
      "id": "9VqgTUzqaoIo",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 281
        },
        "id": "7YHbaOAHatTc",
        "outputId": "2874545b-cbd4-450e-ab7b-35d9f9234d42"
      },
      "source": [
        "df_GA['STAT_CAUSE_DESCR'].value_counts().plot(kind='barh',color='lightblue',title='causes of fires for GA')\n",
        "plt.show()"
      ],
      "id": "7YHbaOAHatTc",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 281
        },
        "id": "YKFM9FT0awfT",
        "outputId": "a50beed7-3852-4f46-b25a-7d8dd538fc32"
      },
      "source": [
        "df_TX['STAT_CAUSE_DESCR'].value_counts().plot(kind='barh',color='lightblue',title='causes of fires for TX')\n",
        "plt.show()"
      ],
      "id": "YKFM9FT0awfT",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 364
        },
        "id": "4Azv0T2pytvx",
        "outputId": "2c6fec93-b76a-4ad3-910e-783903fbde45"
      },
      "source": [
        "# plotting firesize vs firecause\n",
        "df1 = df.groupby('STAT_CAUSE_DESCR').mean()\n",
        "plt.bar(df['STAT_CAUSE_DESCR'].unique(),df1['FIRE_SIZE'])\n",
        "plt.xticks(rotation=90)\n",
        "plt.title('Average Fire size (in acres) v/s Fire Cause')\n",
        "plt.show()\n"
      ],
      "id": "4Azv0T2pytvx",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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t4GDg0ohYE7g0LwNsC6yZb3sDRxUvtZmZ9WvA5B4Rj0TETfn+TOAuYCVgO+DE/LQTge3z/e2AkyK5Dlha0grFS25mZn0aUpu7pInA+sD1wPIR8Uh+6FFg+Xx/JeDBysseyuvMzGyEDDq5S1oC+B1wQEQ8W30sIgKIoWxY0t6SpkiaMmPGjKG81MzMBjCo5C5pIVJi/01E/D6vfqzV3JL/Pp7XPwxMqLx85bxuHhFxbERMiohJ48ePH275zcysg8H0lhFwPHBXRPyw8tDZwO75/u7AWZX1u+VeM5sAz1Sab8zMbAQsOIjnbAZ8DLhN0rS87ivAd4DJkvYE/grslB87D3g3MB34J7BH0RKbmdmABkzuEXE1oD4efkeH5wewb81ymZlZDb5C1cysgZzczcwayMndzKyBnNzNzBrIyd3MrIGc3M3MGsjJ3cysgZzczcwayMndzKyBnNzNzBrIyd3MrIGc3M3MGsjJ3cysgZzczcwayMndzKyBnNzNzBrIyd3MrIGc3M3MGsjJ3cysgZzczcwayMndzKyBnNzNzBrIyd3MrIGc3M3MGmjA5C7pBEmPS7q9su5QSQ9LmpZv76489mVJ0yXdI2nrbhXczMz6Npia+6+BbTqs/1FErJdv5wFIWhvYGXh9fs0vJI0rVVgzMxucAZN7RPwJ+Psg420HnB4Rz0fE/cB0YKMa5TMzs2Go0+a+n6Rbc7PNMnndSsCDlec8lNeZmdkIGm5yPwpYHVgPeAQ4YqgBJO0taYqkKTNmzBhmMczMrJNhJfeIeCwiZkfEi8BxzG16eRiYUHnqynldpxjHRsSkiJg0fvz44RTDzMz6MKzkLmmFyuIOQKsnzdnAzpIWlrQasCZwQ70impnZUC040BMknQZsASwn6SHgEGALSesBATwA7AMQEXdImgzcCcwC9o2I2d0pupmZ9WXA5B4Ru3RYfXw/zz8cOLxOoczMrB5foWpm1kBO7mZmDeTkbmbWQE7uZmYN5ORuZtZATu5mZg3k5G5m1kBO7mZmDeTkbmbWQE7uZmYN5ORuZtZATu5mZg3k5G5m1kBO7mZmDeTkbmbWQE7uZmYN5ORuZtZATu5mZg3k5G5m1kBO7mZmDTTgBNlm9tIz8eBzi8V64DvvKRbLBs81dzOzBnJyNzNrICd3M7MGGjC5SzpB0uOSbq+sW1bSxZLuzX+Xyesl6aeSpku6VdIG3Sy8mZl1Npia+6+BbdrWHQxcGhFrApfmZYBtgTXzbW/gqDLFNDOzoRgwuUfEn4C/t63eDjgx3z8R2L6y/qRIrgOWlrRCqcKamdngDLfNffmIeCTffxRYPt9fCXiw8ryH8jozMxtBtU+oRkQAMdTXSdpb0hRJU2bMmFG3GGZmVjHc5P5Yq7kl/308r38YmFB53sp53Xwi4tiImBQRk8aPHz/MYpiZWSfDTe5nA7vn+7sDZ1XW75Z7zWwCPFNpvjEzsxEy4PADkk4DtgCWk/QQcAjwHWCypD2BvwI75aefB7wbmA78E9ijC2U2M7MBDJjcI2KXPh56R4fnBrBv3UKZmVk9vkLVzKyBnNzNzBrIyd3MrIGc3M3MGsjJ3cysgZzczcwayMndzKyBnNzNzBrIyd3MrIGc3M3MGsjJ3cysgZzczcwayMndzKyBnNzNzBrIyd3MrIGc3M3MGsjJ3cysgZzczcwayMndzKyBnNzNzBrIyd3MrIGc3M3MGsjJ3cysgZzczcwayMndzKyBFqzzYkkPADOB2cCsiJgkaVngDGAi8ACwU0Q8Va+YZmY2FLWSe7ZlRDxRWT4YuDQiviPp4Lz8pQLbMbOKiQefWyzWA995T7FYNjp0o1lmO+DEfP9EYPsubMPMzPpRN7kHcJGkqZL2zuuWj4hH8v1HgeU7vVDS3pKmSJoyY8aMmsUwM7Oqus0ym0fEw5JeCVws6e7qgxERkqLTCyPiWOBYgEmTJnV8jpmZDU+tmntEPJz/Pg6cCWwEPCZpBYD89/G6hTQzs6EZds1d0uLAAhExM99/F3AYcDawO/Cd/PesEgXtFZ+06p8/H3spGgv7fZ1mmeWBMyW14pwaERdIuhGYLGlP4K/ATvWLaTb2jIUEYM017OQeEfcB63ZY/yTwjjqFMjOzenyFqplZAzm5m5k1kJO7mVkDObmbmTWQk7uZWQOVGDisp9zdzMxsfq65m5k1kJO7mVkDObmbmTXQmG9zt+by+RSz4XNyN7MR5x/u7nOzjJlZAzm5m5k1kJO7mVkDObmbmTWQk7uZWQM5uZuZNZC7QppZ47irpZN743knN3tpcrOMmVkDObmbmTWQk7uZWQO5zb3H3CZuZt3gmruZWQN1LblL2kbSPZKmSzq4W9sxM7P5dSW5SxoH/BzYFlgb2EXS2t3YlpmZza9bNfeNgOkRcV9EvACcDmzXpW2ZmVkbRUT5oNKHgG0iYq+8/DFg44jYr/KcvYG98+JrgHuKF2ReywFPjNH4Y7nsjt+72I7fu9gjER9g1YgY3+mBnvWWiYhjgWNHanuSpkTEpLEYfyyX3fF7F9vxexd7JOIPpFvNMg8DEyrLK+d1ZmY2ArqV3G8E1pS0mqSXATsDZ3dpW2Zm1qYrzTIRMUvSfsCFwDjghIi4oxvbGoJuNwF1M/5YLrvj9y624/cu9kjE71dXTqiamVlv+QpVM7MGcnI3M2sgJ3czswbyqJCjkKTbgPaTIc8AU4BvRsSTI1+qoZG0ObBmRPxK0nhgiYi4v9flMnupaPQJVUn7A78CZgK/BNYHDo6IiwrFX7bD6pkR8Z+acb8HzAZOzat2BhYDHgU2j4j31Ymft7E88C1gxYjYNo/9s2lEHF8g9iHAJOA1EbGWpBWB30bEZnVj5/hrAV8EVqVSQYmItxeKvxlwaCW+Uvh4dYn43SbpAx1WPwPcFhGPF4i/GHAgsEpEfFLSmqTv+pwCsbu2X+b4mwHTIuIfkj4KbAD8JCL+WjPuH5m/QjZHRLy/TvxhiYjG3oBb8t+tgd8DrwduKhj/AVISfgJ4Mt9/GLgJeFONuPOVsbWO9A9aouznAztVPqMFC8aeRkqIN1fW3VryewX+izSG0Ztat4Lx7yYNevdK4BWtW4G4M4Fn+7oVLP+5wN+B3+Xbk8BFwL3AxwrEPwM4CLg9Ly9GSpijer9s7Yd531wXuBnYF7iyQNy35dtP8ufzvnw7FfhRqfIP5db0Zhnlv+8GTo6IOySpvxcM0cXA/0TEhQCS3gV8kHS08Atg42HGHSdpo4i4IcfdkHS9AMCsekWeY7mImCzpyzDn2oTZhWK/EBEhKQAkLV4obsusiDiqcMyqZyLi/NJBI2JJAEnfAB4BTibto7sCKxTc1ILA6yLisby95YGTSPvjn/J261g9Ij4saReAiPhnwf+rbu6XkPadkLQd8LOIOF7SnnWDRsSVAJKOiHmHHPijpCl14w9H00+oTpV0ESm5XyhpSeDFgvE3aSV2gEjNPZtGxHXAwjXi7gUcL+l+SQ8AxwOfzEny23UKXPEPSa8gH0pK2oR06F7CZEnHAEtL+iRwCXBcodiQ/mE+LWkFScu2bgXjXy7p+5I2lbRB61Yw/vsj4hcRMTMins0/VCVHTZ3QSuzZ43nd34FaTYbZC5IWZe6+szrwfIG40N39EmBm/uH4KHCupAWAhQrGX1zSnOY7SasBpSs3g9L0mvuewHrAfbl28Qpgj4LxH5H0JdKQxgAfBh7L49kP+0ckIm4E3iDp5Xm5unNPHm7cNp8nDQmxuqRrgPHAh0oEjogfSNqK1NzwGuC/I+LiErGz3fPfL1Y3C5RqE28dcVVrYAEUadMnJbBdSftNALsA/ygUG+AKSecAv83LH8zrFgeeLhD/EOACYIKk3wCbAR8vEBe6uF9mHwY+AuwZEY9KWgX4fsH4nyN91veRjspWBfYpGH/Qmn5C9a2d1kfEnwrFX460o2+eV10DfJ1U01glIqYPM+7CpH/Iicx7wvCwOuWtxB8HfBY4kpR8BdwTNU8EV+IvDvw7ImZLek3exvml4o91kiaS2mY3IyX3a4ADIuKBQvFF2n9aJ7CvAX4XBf/Zc0VpE9K+c11E1B7attv7Zd7Gtu1NbpI+FRFHF9zGwsBr8+LdEVHqqGZo5Wh4cv9jZXER0gm4qVGoV0W3SLqA9AMxlXSSFoCIOKLgNm6IiI1KxWuLPRV4C7AMcDWpC+cLEbFrofgLkU6otn68rwCOKfjj1NUeG00gaSXm761Uu9LUzf0yx78W+H8RcVlePgjYMiK2LRR/MdLRx6pRuCfRkMvS5OTeTtIE4McR8cFC8dYCvsD8NexaPx6Sbo+IdeqVbsBt/IjU1ngGlSaBiLipQOybImIDSZ8BFo2I70maFhHr1Y2d4/+SVPYT86qPAbMjTw5TIP75pJPiX42IdSUtSOr584ZC8RchNRm+nlTpACAiPlEo/geA75J6+4i5XTmXKhT/u6TmjTuY2/wYUaC7Xzf3yxx/OeAcUpPeNqQa9i6RZowrEf8MUqVst4hYJyf7a0vt+0PR9Db3dg8BrysY77fA0aQ+9CXP6F8r6Q0RcVvBmO1aO1u1qadUu7IkbUrqBdLqiTCun+cP1YYRsW5l+TJJtxSM3+0eGyeTultuTfr8dwXuKhj/e8D7IqJkzKrtSbXRbjQ3dHO/JCKekPR+0kn+qcCHSjZX0d2eREPS6OQu6UjmXliwAGnHKVIDyLrVJW9z4OOS7if1QmjVvN5YagMRsWWpWB0cAHwZODN3P301cHnB+LMlrR4RfwHI8Usm32732FgjInaUtF1EnCjpVOCqgvEf62JiB7iPVLsunty7tV9Kmsm8Fxm9jHQC/kOSih3V0N2eREPS6OROauttmQWcFhHXFIz/R0mfBs6k8gXmLmd1FGn/60TSRyPiFEmf7/R4RPyw7jZyn98rK8v3kU6UlfJFUnfFao+Ekr2gut1jo3Vu4GlJ65CuPH5lwfhTcvPAH5h3v/x9ofj/BKZJurQtfu3vWNJ/d1pftzNBRCyZa9ATIuL/6sQaQDd7Eg1Jo5N7rhW9DFgrryo9CXfRLnmSloqIZ0lXMnbLYvnvkqUDa/5LsIN09e7lEXFKqe1ExKWtE1V51T2lmghyj43W1YZd6bEBHCtpGeBrpB+RJfL9UpYiJeB3VdYF6SrtEs6mezOrVbuELgK8l0JNVvnipXOBIudO+tjGxZJuYm5Pov1L9CQajkafUJW0Bemk2wOkD3oCsHuprpClSTonIt6bm2OCuVfYQqGxTSR9NyK+JGnHiPjtwK8YUuy3dVi9LOmCkXsj4uBC29kRuCAiZkr6f6TxQb5Z8KRbV3ts2ODlboUXRsQWheKdSLoy9cYS8frYRld6Eg25HA1P7lOBj0TEPXl5LVLTzJtqxn17RFymzgM0lTz8LU5pxMk3krqElrzqsr9tjsvbK9Vb5taIeKPSyJPfAH5AulBquMM9tMfvdo+Nl5MGJntLXnUF8I22i9WGE/eg3DOpeq5pjrrNJpImR8RO6jxqKSXPCVW2uQxwY0SsUSje3cAawF9J323R81nd7Ek0VI1ulgEWaiV2gIj439xHuq63AZeRBgZqV+Twt4u//hcATwFLSHqWvHND2e5yVZEuZioZsnXy9D3AcRFxrqRvFozf1R4bwAnA7aQBsiB15fwV0LGyMASt5otujWWyf/773i7Fbx/uehzpfMc3Cm5i64KxOulmT6IhaXrN/QTSr2ervXdXYFyp/sTdUvn1v5O5iazor7+ksyKi5HgmfQ2BvAywG6mHSKmLmM4hjb65FalJ5l/ADW3dI0etTn3+C18HsFq0jZ0vacNuNkWUImnVyuIsUs+fUoPltbaxLnOPmq6KiGLdaPM1EjtGxHOlYg67LA1P7guThvRsDQ9wFfCLgiffujJMgKR7gDd2+9df0qtIV+0GKTk+NsBLBorXfq6gdUL1ClKb+LN14le2sxjpApTbIuJeSSsAb4ia4/T31YOopURPorydPwNfjIir8/JmwA8iYtNC8aeSBid7OC+/jdTOXOtEYqU7Yetob85DFDrqk3RyRHxsoHU14u8PfJK5R9c7AMdGxJGF4v+ONJxw8Z5EQ9XoZpmIeF7SUcC51eaZgs5i7jABJRNx1/oRtygNc3oIqXlJwCNA/yMAABVfSURBVJGSDouIE4YbMyJWK1W+vuT2+5siojV2BxHxCGkI3bpaPYheA2zI3B4h7wNuKBC/5VPASbntHVIz2e79PH848f8g6X2kI5tvk0ZGrSXykMVd9vrqQr46uNY5sjZ7AhtHxD9y/O8CfyaNZ1NCN3sSDUmjk3u+Eu37pAsWVpO0HnBYweaNlSNim0KxqrrWj7jiIGD9yFP25Yt2riW1B49auf3+HkmrlO6vHBFfB5D0J2CDiJiZlw8lTYBRW/5x+likYQ2WytstckTTEhE3SvosaYKOfwPvjIgZJWLn8t9R/XEtFPfLwFeARfO5IEiVjheAY0tuinkveJvNvL3SaomIEwd+1shodHIn1Uw3IjULEBHTlMZXLqVbwwSMxK//k8zbn35mXjcWLAPcIekG5vZmiYLnEJYnJZWWF/K62vKP0+b5ftGk3uE6g8VIR5bHS6JEpaZbP64R8W3g25K+HRFfLhW3g18B10s6My9vT5ovoZZe9CQaSNOT+38i4pm2nholTzIUHyYg14w+Ht0dHgBgOmknP4v0mWwH3Npqdy7Vvtwl1Qt+RDo5tnPB+CcBN7QlgF8XjH+zpLNJYxNVu1rW7WX1g5qvH6xOP65FfjxIn/vLW91CJS0NbBERfygQm4j4oaQrmHsebo+IuLlA6APy3671JBqqpp9QPZ50YuNg0onPz5K6R36qUPxVO62P+pPtXgp8oG6/5wG2cUh/j7eaKIYZ+9KIeMdA6+qQtD5p0oUdgfuB35c6KZbjb8DcHhV/KpQAWrF/1WF1lOzFpTRs8YZ58YYoMDF2JXani9XmTDVXM3annkQ3R8T6dWPnWN8gTTV4bavdvVDc1kioxU7+1tX0mvtngK+SatWnARdSts/sNzud2Sf1W67jOeA2SRczb82oWJt7neTdF6WhbBcDlssXn7QOmZYCVioQfy3SrEW7kHrhnEGqoBQ5ymnryvlAvs15LOqPGQRARJQcB2c+knYinWu6grkny78YEf9TIn5EXJkrNmtGxCW591KpUT87Tf1ZMk/dR9p/fpp7/1xF+vE+q2bcl0n6CPDmThc3FjgqG7JG19y7rfVrXVkeR+qet3bNuB17TpQ8WSNpEumHr/1CqTpNSvuTDk9XJPVDbyX3Z0kXG/1s2AVO8V8k/TPuGXmWK0n3RYFhGXKsTl05YW5zW63t9HXlaEupH2+l4Y+3atXWJY0HLil1HYDSvLh7A8tGxOpK4/wcXeLILF+b8jTw87xq37ydj9eN3badV5EuIvsCsEzdnkD5PMquOWb7+bKiR2WD1eiau7o3mUZXz+yP0Bn335AGPLuNQpOGR8RPgJ9I+kzJJpKKD5Da1i9Xmq3qdMr2dOh2V85uXTnaboG2Zpgn6VwjHq59SR0VrgfI1xqUGtXyM6RzKmfk5Yvz9opQmuhlbeAxUkXhQxQYBjxfs3C1pCkxSmbsanTNPddgjmb+6eqmForflTP7lRrkPErVUPM2ro6IzQd+5rDjv5n5f1RPKhR7cdIJ4F1IQwKcRBo7vu5FTK+NiLtze/t8otDYMt0m6fuk8YNOy6s+TDqiPKhQ/OsjYuNWW3jui35TL3qEDFU+Sb4i6ervK0lNMvcVjL84aZLsVSJib3mave6QNDVqDhI2iG0UHwMm9zlvWYR00nDZiOg41vUwt/EOUnJs70tfYlyck4HVgWnMO3xC8av0ctv+jsCH6zYLSDo2/0N2mlgkChzx/TgiDujQZbG1gZLDS1QnyL4qIs7s7/lDjP09UtPJbqSa9qeBOyPiqwViX07nz6bovMeSXkcaZ+ZzpCFJVi4Ud9RMs9f05H4o8DjlJ9Noxf8OqZmga2PAVLZV9IdK0imk+SPbR6+r3TYo6S5g7WjyzjUMkt4UEVO72dukbXtLMW+lo9R+vwDpSs93kZrFLgR+WeL7llTdxxch9XKbVfCo472kXlBvBZYGriP9+BW5eC83y0yq9vCRdEup8x1D0eg2dwpPptHBDnRhBLi2ZoEFgEmU/642jIjXDPy0YbkdeBVlhgToiW40K7WaA0sn8XaS9gG+Tro69UXmjgVTar/fEjglIo4rFG+ODk2m1+T+9KVsQ2pr/0lE/K1g3BZPszcSRuAEWbfGgDmicn8WqUveTp2fOmzXSlo7Iu4sHBdgOeDO/E9ZPWIa8TGth6OvZiVS236J+GuSxntZm1Q7TRsod07lC8A60b0ZgHYDjpL0d3JXQuDqiHiqbuC27qgLkMaVeXkfTx+yiNgvd+NcG/hbTsQLRh5qooBRM81eo5tlAJTmqGz/J6r1T1rp0rYSo2QEuKHKTSerky4AKjoJ90g1O3RLt5uVJF1NSgI/Ig1Ktgeph0uRcyq5J9EHIuKfJeL1s50VSb1NvgCsGBG1K4tt3VFnkfbPw3JvlNq62Y2zso1XMHeaveu6+CPbfzmanNzzVZhbkJL7eaSJp6+OiFqTHffVD72lTlfGnBifiohb88UobwX+QsGhivN2unJ1bVv8eS5yKVg76ipJvwU+G2m0yW7EnxoRb5J0W+RheEueU1G6evdXpK6KxSsdkj5Kard+A+lisqtJ7dZ/rhl3AWDTKDuJffs2ppG7cVbaxOd8DzXi9jurWS96WjW6WYZUq1gXuDki9lC6JLv2RM3d6ocu6eekLmyLKI3pvgTpEG8z0miNRSa7gLlJPPdPXmSApw9JtXZEOjpYidQltVjtqBsqvViWpLvNSs/nRHavpP1IF3wtUSg2wDGkoZyLXcPQ5sekCsfRpMnPHygRNCJelPQzoMhQA314PiJeUB5vKnfjLFHDbTWlLkI6R3YLqeb+RtL1DUXG6h+Kpif3f+UdZlbuOfA4aZLsItR5BLhnSF/mNyMPpzsEW0bE2kqX8T8MvDLSKHzHALfWL/FcSsMhH0Hq8/s4qTvnXbSNpz1M3bzIpZvOJo3+eFXb+rdQ9uTw/qRhGj5LGg7j7aR27FIWioh+Jx6pIyKWk/R60lHl4blp454oM6bKpbkb5++71Cx2paTWBYhbkbpx/rFu0MhDYEj6PWm46Nvy8jqk+XJHXNOT+xSlUeWOI/U9fY40MH8p55NOuJ2al3cm/dM+ShpFsNMcq/35N0BE/FvSXyNidl4OSf8pUuK5vkFqF7wkX4iyJfDRQrG7VTvqtu2AL0fbEM75xOG3KDA0LKTx1vPd54A9lIat2Jn8Y1jA+ZL2JiWtbnQBXgpYhVQhmEg64VnqCGEf4PPALEn/huJz+34J2It0VLMPqbn2l4ViQ+o9N2f/iYjbc5/6EdfoNvcqSROBpSKiWA1YbWPLVNcNpx1P0kPAD0k79OfyffLyARFR8qij1R/3FtKkHS+W6o/bzYtcuknSjRGxYR+PlWiXXYp0VLMS6SihdWn9gcCtUWg8+nxSEtp+UEv1xpF0K6md/WrSFZ4PlYjbberSRCNt2ziNNNhfdd7mJSJil25tsy+NrLn3d3JD0gYFT26Mk7RRRNyQY2/I3NHxhjOp73HMneqteh/K1i4Anpa0BKkb228kPU5lBMqaDiZd5NKt2lG3LN3PY4sWiH8yaUq9P5Nqj18h/XDvEBHT6gbP+9+DrS7A+cT/B0ldaQ+tG7+l1aMq7z9FqYvDRUcXZ/Gq2AP4L1LTG6T/r6O6tK1+NbLmrs6Xj7dEFLqUOf8znUA6GSbS6Id7ka76fE9ETC6xnZIkrUFqV54G/IvUl3hX0iH2uR0uInnJyLWuy9ovzpG0F2mUxQ/XjF/tHTOO1I6/SkT8u07cSvybSFPq/V3SW0kDq30GWA94Xd1eYpXtrEP6oVqWtN/PAHaPiNtrxGwNF305qYdbdbjoC0rVtpWmUFyfNCdu6YlGRpVGJveRpjzRcXRxco1SJJ1D53blNwDfioihnifotI33ktr0W2PulG437Yrcm+pM0uierR+5SaQ5eHeIiEdrxm8fInq+Zr2a8ec0q+WeVzMi4tC8PN8kGDW2cy3w1Yi4PC9vQdp33lwjZvtw0S0zKTBcdGU7Xb0GQ9JmpKOk9vGmig36N+iyNDG5q8Ng+VVRc3AsSR+NiFOUp6TrEH/UTlHX7XblHGc6aXje27p1IVA35ZPL6+TFOyLiskJxZzO3tihSU88/KfTjJ+l2YL2ImCXpbmDvyIPYSbo9ItbpP8KgtzPfuZm652vyUfBDwIci4sj2JqVSJ4O7LX/un2P+kWhHfH7iRra5038vlQDqjny4eP7baYD/0Z7Mut2uDPAgcPtYTOwAuUbaX9PecOOWmq2oL6eRuvo9QWpyuwrmNMWVPKq8T9LXSE0zkHpZ1R029xhSk9KRuUnp28xtUjqWdM3KsCkPca00+1J1vyx9VPlMRJxfKFYtjay595KkAyLixzVj7E+6wnAm6UTk+sDBUXO88hy7q+3KOdaGpGaZK5m3K96oPaJpCkmbACsAF0WeI1Rp0polSnUkUBpm+eukSaaD9CPy9agxtky3m5QkrRqFrr4eYDvfIXWq+D3z7vsjfoVqo5N7bkP9Fmnci20lrU26vLlrM6VI+r+IWKVmjFsiYl1JW5N6m3wNOLlE+2y325XzNi4izwNLpf9zdGHeVhs5+aTnp4A1SN/tCRFR5PqLbjcpVc9vSPpdRHywfqk7bqcrcwEMR1ObZVp+TaoBt/pX/y9p+q5uToNVYtq3Vox3k5L6HWpdEVRTRDxGmsS32q58bql25WzFUu27NqqcCPyHVFPfFngd6SRoCd1uUqr+/3Tt5GYUmqy9hKYn9+UiYrLSnKfkWsHsgV5UU4lDoam59rsa8GVJS1J4jJButStn50l6V4lmJBtV1q505Tye1J2wiIg4XNKlzG1Sav0fLUBqe6+9iT7uF9Ghc0WQB1WLiPs7vKTrmp7c/6E0/GZr4PxNKFAL6HBSZs5DlDkpuSfpRNJ9EfHP/B72KBB3pPwX8AVJL5BqejAGukLagOY0weSKUtHgEXFdh3X/Wyj8ukqT2Yv5J7YvsW926lwxEfiqpEMj4vSa8Yes6W3uGwBHkpofbgfGk7paFR2EqxQ1ZIJma6Zud+VsIqXJRy4peT3DoLfd5OQOcwateg1pB7yn1AmgblCXJ2geSflagzm9KSLiDz0ukllPqDKf6ohut8nJXdK+wG8i4um8vAywS0T8orcl65tGYMKCbpP0C1KPitPyqg8Df4mIfXtXKrORlzsufK0XFbOmJ/f5+sf26ld0KMZCGfuTu7K9rnVSLP9g3RERPRn61Kzb1Hluh2WBvwG7RcTdI12mpp9QHSdJlSQzjtSfe7Tr9oQF3TadNN5366KRCXmdWVO9t205gCdbF5L1QtNr7t8nDeBzTF61D2lI1AN7V6qB5d44i5PGpvgXY+yElaQrgQ1JXeWCNCvTFHJPpWjgCHz20iZpKml8+/OBK6LQSJ91ND25L0Cay/OdedXFwC8jz3Bk3dHXyHstpUbgMxstcseNzYFtgC2BJ4ELgfMLduccWpmanNyrcpeklUdrN8h27m1iNnZJWpGU6LchdS64LiI+PaJlaHJyl3QF8H7SuYWppImgr42Iz/WyXAMZq71NRnDkPbMxo1c94Jqe3G+ONPnzXsCEiDhE0q2RpwkbrdzbxGxskvRH5u818wzpnNMxI9kWv8BIbahHFpS0ArATcE6vCzMErd4mLWOqt4mkVTrdel0usxFwH2lE1OPy7VnS0N1r5eUR0/SukIeRTmpcHRE3Sno1cG+Py9Snyq/+ksBdklq9TTam4CBNI+Dcyv1FSAOg3QO8vjfFMRsxb455Zzr7Y2v2M0l3jGRBGp3cI+K3wG8ry/eRpu4arX7Q6wKUEG1T9eWxckb0ZJJZjywhaZWI+D9IR7HAEvmxF0ayII1M7pIOiojvSTqSDqM3RsRne1CsAVW7CEpaFVgzIi6RtChj+LuKiJskbdzrcpiNgAOBqyX9hdSRYDXg05IWJ42HP2LGbMIYwF3575SelmKYJH2S1D9/WWB1YGXgaOAdvSzXYLWNbb0AsAHpMmyzRouI8yStCbw2r7qnchK11vSbQ9Xo3jJjlaRppKs6r2+NMSPptvbmjtFK0iGVxVmkGex/Nxqu2jPrNklvJo3lPqfyHBEnjXQ5Gllzl3R2f4+Pgcvfn4+IF1qTIeSr38bMr7DnSrWXKkknk462p5GGD4H0v+vkXsimwIOki4Cup8y8piPpSklfIc0YsxXpZOQfe1ymQeujr+8cY+DH1Wy4JpGmI+x5Zaypyf1VwFbALsBHSF3zTouIEe2KVMPBpKn2biMNdnYe8Muelmho7iN9B6fk5V2AxwAPoWBNdztp33+k1wVpfJu7pIVJyeX7wNcj4mc9LtKgSBoPEBEzel2WoZI0JSImDbTOrGnyLGrrka5Leb61vhdHq02tubeS+ntIiX0i8FPgzF6WaSBKjeyHAPuRrx7O81YeGRGH9bJsQ7S4pFfn6wqQtBppCGOzpju01wVoaWTNXdJJpEmxzwNOj4jbe1ykQcldCLcF9o6I+/O6VwNHARdExI96Wb7BkrQNcCypeUakMfX3iYgLe1ows5eQpib3F5k7S/uYGZ1Q0s3AVhHxRNv68cBFY2nqvXzk1Orre3dEPN/f883GstE4ImojBw6LiAUiYsl8W6pyW3K0JvZsofbEDnPa3RfqQXmGRNJBlcX3R8Qt+fa8pG/1rGBmXRYRm+e/oybnNDK5j2H9jT0xouNSDNPOlftfbntsm5EsiFkvSFo9H7UiaQtJn5W0dC/K4uQ+uqwr6dkOt5nAWLg6VX3c77Rs1kS/A2ZLWoN03mkCcGovCtLY3jJjUUSM63UZaoo+7ndaNmuiFyNilqQdSL3cjszn0kack7uVtK6kZ0m19EXzffLyIr0rltmI+Y+kXYDdgffldT05X+bkbsU04MjDrK49gE8Bh0fE/fkaj5N7UZBGdoU0M+s1ScuQ5m6+tRfb9wlVM7NCJF0haSlJywI3AcdJ+mEvyuLkbmZWzssj4lngA8BJEbEx8M5eFMTJ3cysnAUlrQDsBJzTy4I4uZuZlXMYcCEwPSJuzGND3duLgviEqplZA7krpJlZTZIOiojvSTqSDhfsRcRnR7pMTu5mZvXdlf9O6WkpKtwsY2bWQK65m5nVJOns/h73NHtmZmPTpsCDwGnA9YyCUVDdLGNmVpOkccBWpDmb3wicC5wWEXf0qkzu525mVlNEzI6ICyJid2ATYDpwhaT9elUmN8uYmRWQZ2B6D6n2PhH4KXBmz8rjZhkzs3oknQSsA5wHnB4Rt/e4SE7uZmZ1SXoR+EderCZVAdGLSbKd3M3MGsgnVM3MGsjJ3cysgZzczcwayMndzKyBnNzNzBro/wMWJleXLHRzfwAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "iGkAOzcka7--"
      },
      "source": [
        "Causes of fire vary state by state, so location will be critical attribute in prediction."
      ],
      "id": "iGkAOzcka7--"
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "69s3lmvoD5go"
      },
      "source": [
        "# Visualising the Dataset:\n"
      ],
      "id": "69s3lmvoD5go"
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Zjal5fZC0_2v"
      },
      "source": [
        "le = preprocessing.LabelEncoder()\n",
        "df['STAT_CAUSE_DESCR'] = le.fit_transform(df['STAT_CAUSE_DESCR'])\n",
        "df['STATE'] = le.fit_transform(df['STATE'])\n",
        "df.rename(columns = {\"STAT_CAUSE_DESCR\":\"CAUSE\"}, inplace=\"True\")"
      ],
      "id": "Zjal5fZC0_2v",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "id": "PTbUc9_J1FI3",
        "outputId": "5fece0a4-5ced-4379-9b4e-7f3278e463a2"
      },
      "source": [
        "df.head()"
      ],
      "id": "PTbUc9_J1FI3",
      "execution_count": null,
      "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>FOD_ID</th>\n",
              "      <th>FIRE_YEAR</th>\n",
              "      <th>MONTH</th>\n",
              "      <th>START_DATE</th>\n",
              "      <th>DISCOVERY_TIME</th>\n",
              "      <th>END_DATE</th>\n",
              "      <th>CONT_TIME</th>\n",
              "      <th>FIRE_SIZE</th>\n",
              "      <th>FIRE_SIZE_CLASS</th>\n",
              "      <th>LATITUDE</th>\n",
              "      <th>LONGITUDE</th>\n",
              "      <th>STATE</th>\n",
              "      <th>COUNTY</th>\n",
              "      <th>CAUSE</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>2005</td>\n",
              "      <td>2</td>\n",
              "      <td>2005-02-02</td>\n",
              "      <td>1300</td>\n",
              "      <td>2005-02-02</td>\n",
              "      <td>1730</td>\n",
              "      <td>0.10</td>\n",
              "      <td>A</td>\n",
              "      <td>40.036944</td>\n",
              "      <td>-121.005833</td>\n",
              "      <td>4</td>\n",
              "      <td>63</td>\n",
              "      <td>7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>2004</td>\n",
              "      <td>5</td>\n",
              "      <td>2004-05-12</td>\n",
              "      <td>0845</td>\n",
              "      <td>2004-05-12</td>\n",
              "      <td>1530</td>\n",
              "      <td>0.25</td>\n",
              "      <td>A</td>\n",
              "      <td>38.933056</td>\n",
              "      <td>-120.404444</td>\n",
              "      <td>4</td>\n",
              "      <td>61</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>2004</td>\n",
              "      <td>5</td>\n",
              "      <td>2004-05-31</td>\n",
              "      <td>1921</td>\n",
              "      <td>2004-05-31</td>\n",
              "      <td>2024</td>\n",
              "      <td>0.10</td>\n",
              "      <td>A</td>\n",
              "      <td>38.984167</td>\n",
              "      <td>-120.735556</td>\n",
              "      <td>4</td>\n",
              "      <td>17</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>2004</td>\n",
              "      <td>6</td>\n",
              "      <td>2004-06-28</td>\n",
              "      <td>1600</td>\n",
              "      <td>2004-07-03</td>\n",
              "      <td>1400</td>\n",
              "      <td>0.10</td>\n",
              "      <td>A</td>\n",
              "      <td>38.559167</td>\n",
              "      <td>-119.913333</td>\n",
              "      <td>4</td>\n",
              "      <td>3</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>2004</td>\n",
              "      <td>6</td>\n",
              "      <td>2004-06-28</td>\n",
              "      <td>1600</td>\n",
              "      <td>2004-07-03</td>\n",
              "      <td>1200</td>\n",
              "      <td>0.10</td>\n",
              "      <td>A</td>\n",
              "      <td>38.559167</td>\n",
              "      <td>-119.933056</td>\n",
              "      <td>4</td>\n",
              "      <td>3</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   FOD_ID  FIRE_YEAR  MONTH START_DATE  ...   LONGITUDE STATE COUNTY  CAUSE\n",
              "0       1       2005      2 2005-02-02  ... -121.005833     4     63      7\n",
              "1       2       2004      5 2004-05-12  ... -120.404444     4     61      6\n",
              "2       3       2004      5 2004-05-31  ... -120.735556     4     17      3\n",
              "3       4       2004      6 2004-06-28  ... -119.913333     4      3      6\n",
              "4       5       2004      6 2004-06-28  ... -119.933056     4      3      6\n",
              "\n",
              "[5 rows x 14 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kfcKRptX09TK"
      },
      "source": [
        "df['DAY_OF_WEEK'] = pd.DatetimeIndex(df['START_DATE']).weekday"
      ],
      "id": "kfcKRptX09TK",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 500
        },
        "id": "Zkc28mp-0IOs",
        "outputId": "fa2dea01-f183-4a20-f446-ffbe2db285b8"
      },
      "source": [
        "#Corralation\n",
        "plt.figure(figsize=(12, 8))\n",
        "df_copy = df.drop('FOD_ID', axis=1)\n",
        "corr = df_copy.corr()\n",
        "sb.heatmap(corr, annot=True)\n",
        "plt.title('Correalation Matrix')\n",
        "plt.show()\n"
      ],
      "id": "Zkc28mp-0IOs",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x576 with 2 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 309
        },
        "id": "Xl1awiub2Ph6",
        "outputId": "e7b54645-3886-4517-8840-225e00949922"
      },
      "source": [
        "df.head()"
      ],
      "id": "Xl1awiub2Ph6",
      "execution_count": null,
      "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>FOD_ID</th>\n",
              "      <th>FIRE_YEAR</th>\n",
              "      <th>MONTH</th>\n",
              "      <th>START_DATE</th>\n",
              "      <th>DISCOVERY_TIME</th>\n",
              "      <th>END_DATE</th>\n",
              "      <th>CONT_TIME</th>\n",
              "      <th>FIRE_SIZE</th>\n",
              "      <th>FIRE_SIZE_CLASS</th>\n",
              "      <th>LATITUDE</th>\n",
              "      <th>LONGITUDE</th>\n",
              "      <th>STATE</th>\n",
              "      <th>COUNTY</th>\n",
              "      <th>CAUSE</th>\n",
              "      <th>DAY_OF_WEEK</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>2005</td>\n",
              "      <td>2</td>\n",
              "      <td>2005-02-02</td>\n",
              "      <td>1300</td>\n",
              "      <td>2005-02-02</td>\n",
              "      <td>1730</td>\n",
              "      <td>0.10</td>\n",
              "      <td>A</td>\n",
              "      <td>40.036944</td>\n",
              "      <td>-121.005833</td>\n",
              "      <td>4</td>\n",
              "      <td>63</td>\n",
              "      <td>7</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>2004</td>\n",
              "      <td>5</td>\n",
              "      <td>2004-05-12</td>\n",
              "      <td>0845</td>\n",
              "      <td>2004-05-12</td>\n",
              "      <td>1530</td>\n",
              "      <td>0.25</td>\n",
              "      <td>A</td>\n",
              "      <td>38.933056</td>\n",
              "      <td>-120.404444</td>\n",
              "      <td>4</td>\n",
              "      <td>61</td>\n",
              "      <td>6</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>2004</td>\n",
              "      <td>5</td>\n",
              "      <td>2004-05-31</td>\n",
              "      <td>1921</td>\n",
              "      <td>2004-05-31</td>\n",
              "      <td>2024</td>\n",
              "      <td>0.10</td>\n",
              "      <td>A</td>\n",
              "      <td>38.984167</td>\n",
              "      <td>-120.735556</td>\n",
              "      <td>4</td>\n",
              "      <td>17</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>2004</td>\n",
              "      <td>6</td>\n",
              "      <td>2004-06-28</td>\n",
              "      <td>1600</td>\n",
              "      <td>2004-07-03</td>\n",
              "      <td>1400</td>\n",
              "      <td>0.10</td>\n",
              "      <td>A</td>\n",
              "      <td>38.559167</td>\n",
              "      <td>-119.913333</td>\n",
              "      <td>4</td>\n",
              "      <td>3</td>\n",
              "      <td>6</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>2004</td>\n",
              "      <td>6</td>\n",
              "      <td>2004-06-28</td>\n",
              "      <td>1600</td>\n",
              "      <td>2004-07-03</td>\n",
              "      <td>1200</td>\n",
              "      <td>0.10</td>\n",
              "      <td>A</td>\n",
              "      <td>38.559167</td>\n",
              "      <td>-119.933056</td>\n",
              "      <td>4</td>\n",
              "      <td>3</td>\n",
              "      <td>6</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   FOD_ID  FIRE_YEAR  MONTH START_DATE  ... STATE COUNTY CAUSE  DAY_OF_WEEK\n",
              "0       1       2005      2 2005-02-02  ...     4     63     7            2\n",
              "1       2       2004      5 2004-05-12  ...     4     61     6            2\n",
              "2       3       2004      5 2004-05-31  ...     4     17     3            0\n",
              "3       4       2004      6 2004-06-28  ...     4      3     6            0\n",
              "4       5       2004      6 2004-06-28  ...     4      3     6            0\n",
              "\n",
              "[5 rows x 15 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZrvcBVMS2tew"
      },
      "source": [
        "X = df.drop(['FOD_ID','START_DATE','DISCOVERY_TIME','END_DATE','CONT_TIME','FIRE_SIZE_CLASS','COUNTY','CAUSE'], axis=1).values\n",
        "y = df['CAUSE'].values"
      ],
      "id": "ZrvcBVMS2tew",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HvY7BEJq3zM3"
      },
      "source": [
        "from sklearn import tree, preprocessing\n",
        "import sklearn.ensemble as ske\n",
        "from sklearn.model_selection import train_test_split "
      ],
      "id": "HvY7BEJq3zM3",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ww2L5wT33_C7"
      },
      "source": [
        "X_train, X_test, y_train, y_test = train_test_split(X,y,test_size=0.3, random_state=0) "
      ],
      "id": "ww2L5wT33_C7",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zYFRSV3x4Ggc"
      },
      "source": [
        "model1 = ske.RandomForestClassifier(n_estimators=50)\n",
        "model1 = model1.fit(X_train, y_train)\n",
        "print(model1.score(X_test,y_test))"
      ],
      "id": "zYFRSV3x4Ggc",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fYEfa7SP6ZBr",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "ca12fd64-4471-4c0c-f5ad-a99899d409d1"
      },
      "source": [
        "def set_label(cat):\n",
        "    cause = 0\n",
        "    natural = ['Lightning']\n",
        "    accidental = ['Structure','Fireworks','Powerline','Railroad','Smoking','Children','Campfire','Equipment Use','Debris Burning']\n",
        "    malicious = ['Arson']\n",
        "    other = ['Missing/Undefined','Miscellaneous']\n",
        "    if cat in natural:\n",
        "        cause = 1\n",
        "    elif cat in accidental:\n",
        "        cause = 2\n",
        "    elif cat in malicious:\n",
        "        cause = 3\n",
        "    else:\n",
        "        cause = 4\n",
        "    return cause\n",
        "     \n",
        "\n",
        "df['LABEL'] = df_original['STAT_CAUSE_DESCR'].apply(lambda x: set_label(x)) # I created a copy of the original df earlier in the kernel\n",
        "df = df.drop('CAUSE',axis=1)\n",
        "print(df.head())"
      ],
      "id": "fYEfa7SP6ZBr",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "   FOD_ID  FIRE_YEAR  MONTH START_DATE  ...   LONGITUDE STATE COUNTY  LABEL\n",
            "0       1       2005      2 2005-02-02  ... -121.005833     4     63      4\n",
            "1       2       2004      5 2004-05-12  ... -120.404444     4     61      1\n",
            "2       3       2004      5 2004-05-31  ... -120.735556     4     17      2\n",
            "3       4       2004      6 2004-06-28  ... -119.913333     4      3      1\n",
            "4       5       2004      6 2004-06-28  ... -119.933056     4      3      1\n",
            "\n",
            "[5 rows x 14 columns]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rABwtISsFgZ_",
        "outputId": "a8463a86-4a5c-4b72-eb63-b2c932669fff"
      },
      "source": [
        "df['LABEL'].value_counts()"
      ],
      "id": "rABwtISsFgZ_",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "2    830014\n",
              "4    490528\n",
              "3    281455\n",
              "1    278468\n",
              "Name: LABEL, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "D-f8FGZt6tSV",
        "outputId": "faed0c99-cc1b-4413-c993-cc6d1e03fc2a"
      },
      "source": [
        "X = df.drop(['FOD_ID','START_DATE','DISCOVERY_TIME','END_DATE','CONT_TIME','FIRE_SIZE_CLASS','COUNTY','LABEL'], axis=1).values\n",
        "y = df['LABEL'].values\n",
        "print(y)\n",
        "#print(df.columns)"
      ],
      "id": "D-f8FGZt6tSV",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[4 1 2 ... 4 4 4]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0XtXIA837gSf",
        "outputId": "b118b9d0-d108-4857-ae6f-74079fd6f322"
      },
      "source": [
        "X_train, X_test, y_train, y_test = train_test_split(X,y,test_size=0.3, random_state=0)\n",
        "model2 = ske.RandomForestClassifier(n_estimators=50)\n",
        "model2 = model2.fit(X_train, y_train)\n",
        "print(model2.score(X_test,y_test))"
      ],
      "id": "0XtXIA837gSf",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0.6959105895699649\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "M8bag2HMfNKm",
        "outputId": "dc388fb6-cd99-4fe0-86cc-f33659bf1509"
      },
      "source": [
        "from sklearn.metrics import confusion_matrix\n",
        "y_pred = model2.fit(X_train, y_train).predict(X_test)\n",
        "#y_pred = model2.predict(X_test)\n",
        "cm = confusion_matrix(y_true=y_test,y_pred=y_pred)\n",
        "print(cm)"
      ],
      "id": "M8bag2HMfNKm",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[ 65901  11512   1033   4870]\n",
            " [ 11146 196655  18223  23304]\n",
            " [  1611  34437  40494   7628]\n",
            " [  6812  44943   5900  89671]]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 606
        },
        "id": "PwaX9AdQhb6X",
        "outputId": "11f12bac-fa82-4e94-fb1b-5e3906badf24"
      },
      "source": [
        "cmn = cm.astype('float') / cm.sum(axis=1)[:, np.newaxis]\n",
        "fig,ax = plt.subplots(figsize=(10,10))\n",
        "ax.matshow(cmn,cmap=plt.cm.Oranges,alpha=0.7)\n",
        "for i in range(cmn.shape[0]):\n",
        "    for j in range(cmn.shape[1]):\n",
        "        ax.text(x=j,y=i,s=cmn[i,j],va='center',ha='center')\n",
        "plt.xlabel('predicted label')\n",
        "plt.ylabel('true label')\n",
        "plt.show()"
      ],
      "id": "PwaX9AdQhb6X",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 296
        },
        "id": "zTGuZhvFhpCE",
        "outputId": "564e4647-c7fb-4533-fa48-c330d943c956"
      },
      "source": [
        "cm_rfc = confusion_matrix(y_test,y_pred,normalize='true')\n",
        "disp = ConfusionMatrixDisplay(confusion_matrix=cm_rfc,display_labels=['natural','accidental','malicious','other'])\n",
        "disp.plot()"
      ],
      "id": "zTGuZhvFhpCE",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<sklearn.metrics._plot.confusion_matrix.ConfusionMatrixDisplay at 0x7f6917957910>"
            ]
          },
          "metadata": {},
          "execution_count": 37
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    }
  ]
}