pet_finder.ipynb

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  "metadata": {
    "colab": {
      "name": "pet_finder.ipynb",
      "provenance": [],
      "collapsed_sections": [
        "uwcmnSJUzR8b",
        "dGqpjxMGzZb7",
        "NmDgYtX4NcLo"
      ],
      "toc_visible": true,
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/george-zakharov/ml_notebooks/blob/master/pet_finder.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "j6T4d_zHzAmM",
        "colab_type": "text"
      },
      "source": [
        "**Homework 2 Pro: Pet Finder Dataset (binary classification)**\n",
        "\n",
        "https://www.kaggle.com/c/petfinder-adoption-prediction/data"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uwcmnSJUzR8b",
        "colab_type": "text"
      },
      "source": [
        "# Load libs"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EXp-d9nqyqcg",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "from sklearn.neighbors import KNeighborsClassifier\n",
        "from sklearn.naive_bayes import BernoulliNB, ComplementNB, GaussianNB, MultinomialNB\n",
        "from sklearn.metrics import accuracy_score\n",
        "from sklearn.model_selection import train_test_split, cross_val_score, GridSearchCV\n",
        "from sklearn.model_selection import KFold\n",
        "import sklearn\n",
        "import numpy as np\n",
        "from google.colab import files\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZEJfSUR-K2_l",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 122
        },
        "outputId": "a0ec3b86-2db1-40e4-da6c-e0b917c3e8b4"
      },
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Go to this URL in a browser: https://accounts.google.com/o/oauth2/auth?client_id=947318989803-6bn6qk8qdgf4n4g3pfee6491hc0brc4i.apps.googleusercontent.com&redirect_uri=urn%3aietf%3awg%3aoauth%3a2.0%3aoob&response_type=code&scope=email%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdocs.test%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdrive%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdrive.photos.readonly%20https%3a%2f%2fwww.googleapis.com%2fauth%2fpeopleapi.readonly\n",
            "\n",
            "Enter your authorization code:\n",
            "··········\n",
            "Mounted at /content/drive\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "dGqpjxMGzZb7",
        "colab_type": "text"
      },
      "source": [
        "# Load dataset"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2d0jH0V8LE6O",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "df_train  = pd.read_csv('/content/drive/My Drive/Colab Notebooks/ML/2/train.csv')\n",
        "df_test   = pd.read_csv('/content/drive/My Drive/Colab Notebooks/ML/2/test.csv')\n",
        "labels_breed = pd.read_csv('/content/drive/My Drive/Colab Notebooks/ML/2/breed_labels.csv')\n",
        "labels_state = pd.read_csv('/content/drive/My Drive/Colab Notebooks/ML/2/color_labels.csv')\n",
        "labels_color = pd.read_csv('/content/drive/My Drive/Colab Notebooks/ML/2/state_labels.csv')\n",
        "df_train_full = pd.read_csv('/content/drive/My Drive/Colab Notebooks/ML/2/train_full.csv')"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "1JfZMkktMBWA",
        "colab_type": "text"
      },
      "source": [
        "# Data exploration"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hgHuZQ_2LlcY",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 479
        },
        "outputId": "a3e5d7cc-d9ff-4d57-d219-ca1088fe5d2c"
      },
      "source": [
        "df_train.head()"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Type</th>\n",
              "      <th>Name</th>\n",
              "      <th>Age</th>\n",
              "      <th>Breed1</th>\n",
              "      <th>Breed2</th>\n",
              "      <th>Gender</th>\n",
              "      <th>Color1</th>\n",
              "      <th>Color2</th>\n",
              "      <th>Color3</th>\n",
              "      <th>MaturitySize</th>\n",
              "      <th>FurLength</th>\n",
              "      <th>Vaccinated</th>\n",
              "      <th>Dewormed</th>\n",
              "      <th>Sterilized</th>\n",
              "      <th>Health</th>\n",
              "      <th>Quantity</th>\n",
              "      <th>Fee</th>\n",
              "      <th>State</th>\n",
              "      <th>RescuerID</th>\n",
              "      <th>VideoAmt</th>\n",
              "      <th>Description</th>\n",
              "      <th>PetID</th>\n",
              "      <th>PhotoAmt</th>\n",
              "      <th>AdoptionSpeed</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2</td>\n",
              "      <td>Nibble</td>\n",
              "      <td>3</td>\n",
              "      <td>299</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>7</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>100</td>\n",
              "      <td>41326</td>\n",
              "      <td>8480853f516546f6cf33aa88cd76c379</td>\n",
              "      <td>0</td>\n",
              "      <td>Nibble is a 3+ month old ball of cuteness. He ...</td>\n",
              "      <td>86e1089a3</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>No Name Yet</td>\n",
              "      <td>1</td>\n",
              "      <td>265</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>41401</td>\n",
              "      <td>3082c7125d8fb66f7dd4bff4192c8b14</td>\n",
              "      <td>0</td>\n",
              "      <td>I just found it alone yesterday near my apartm...</td>\n",
              "      <td>6296e909a</td>\n",
              "      <td>2.0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1</td>\n",
              "      <td>Brisco</td>\n",
              "      <td>1</td>\n",
              "      <td>307</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>7</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
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              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>41326</td>\n",
              "      <td>fa90fa5b1ee11c86938398b60abc32cb</td>\n",
              "      <td>0</td>\n",
              "      <td>Their pregnant mother was dumped by her irresp...</td>\n",
              "      <td>3422e4906</td>\n",
              "      <td>7.0</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1</td>\n",
              "      <td>Miko</td>\n",
              "      <td>4</td>\n",
              "      <td>307</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>150</td>\n",
              "      <td>41401</td>\n",
              "      <td>9238e4f44c71a75282e62f7136c6b240</td>\n",
              "      <td>0</td>\n",
              "      <td>Good guard dog, very alert, active, obedience ...</td>\n",
              "      <td>5842f1ff5</td>\n",
              "      <td>8.0</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1</td>\n",
              "      <td>Hunter</td>\n",
              "      <td>1</td>\n",
              "      <td>307</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>41326</td>\n",
              "      <td>95481e953f8aed9ec3d16fc4509537e8</td>\n",
              "      <td>0</td>\n",
              "      <td>This handsome yet cute boy is up for adoption....</td>\n",
              "      <td>850a43f90</td>\n",
              "      <td>3.0</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   Type         Name  Age  ...      PetID  PhotoAmt  AdoptionSpeed\n",
              "0     2       Nibble    3  ...  86e1089a3       1.0              2\n",
              "1     2  No Name Yet    1  ...  6296e909a       2.0              0\n",
              "2     1       Brisco    1  ...  3422e4906       7.0              3\n",
              "3     1         Miko    4  ...  5842f1ff5       8.0              2\n",
              "4     1       Hunter    1  ...  850a43f90       3.0              2\n",
              "\n",
              "[5 rows x 24 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8fDmXzRBLvfo",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 513
        },
        "outputId": "578d8f35-dfef-45b4-c66c-63d65702991a"
      },
      "source": [
        "df_test.head()"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Type</th>\n",
              "      <th>Name</th>\n",
              "      <th>Age</th>\n",
              "      <th>Breed1</th>\n",
              "      <th>Breed2</th>\n",
              "      <th>Gender</th>\n",
              "      <th>Color1</th>\n",
              "      <th>Color2</th>\n",
              "      <th>Color3</th>\n",
              "      <th>MaturitySize</th>\n",
              "      <th>FurLength</th>\n",
              "      <th>Vaccinated</th>\n",
              "      <th>Dewormed</th>\n",
              "      <th>Sterilized</th>\n",
              "      <th>Health</th>\n",
              "      <th>Quantity</th>\n",
              "      <th>Fee</th>\n",
              "      <th>State</th>\n",
              "      <th>RescuerID</th>\n",
              "      <th>VideoAmt</th>\n",
              "      <th>Description</th>\n",
              "      <th>PetID</th>\n",
              "      <th>PhotoAmt</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2</td>\n",
              "      <td>Dopey &amp; Grey</td>\n",
              "      <td>8</td>\n",
              "      <td>266</td>\n",
              "      <td>266</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>6</td>\n",
              "      <td>7</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>41326</td>\n",
              "      <td>2ece3b2573dcdcebd774e635dca15fd9</td>\n",
              "      <td>0</td>\n",
              "      <td>Dopey Age: 8mths old Male One half of a pair, ...</td>\n",
              "      <td>e2dfc2935</td>\n",
              "      <td>2.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>Chi Chi</td>\n",
              "      <td>36</td>\n",
              "      <td>285</td>\n",
              "      <td>264</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>7</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>41326</td>\n",
              "      <td>2ece3b2573dcdcebd774e635dca15fd9</td>\n",
              "      <td>0</td>\n",
              "      <td>Please note that Chichi has been neutered, the...</td>\n",
              "      <td>f153b465f</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2</td>\n",
              "      <td>Sticky</td>\n",
              "      <td>2</td>\n",
              "      <td>265</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>6</td>\n",
              "      <td>7</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>200</td>\n",
              "      <td>41326</td>\n",
              "      <td>e59c106e9912fa30c898976278c2e834</td>\n",
              "      <td>0</td>\n",
              "      <td>Sticky, named such because of his tendency to ...</td>\n",
              "      <td>3c90f3f54</td>\n",
              "      <td>4.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1</td>\n",
              "      <td>Dannie &amp; Kass [In Penang]</td>\n",
              "      <td>12</td>\n",
              "      <td>307</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>5</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>41326</td>\n",
              "      <td>e59c106e9912fa30c898976278c2e834</td>\n",
              "      <td>0</td>\n",
              "      <td>Dannie and Kass are mother and daughter. We en...</td>\n",
              "      <td>e02abc8a3</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2</td>\n",
              "      <td>Cuddles</td>\n",
              "      <td>12</td>\n",
              "      <td>265</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>7</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>41326</td>\n",
              "      <td>e59c106e9912fa30c898976278c2e834</td>\n",
              "      <td>0</td>\n",
              "      <td>Extremely cuddly cat, hence the origin of his ...</td>\n",
              "      <td>09f0df7d1</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   Type                       Name  ...      PetID  PhotoAmt\n",
              "0     2               Dopey & Grey  ...  e2dfc2935       2.0\n",
              "1     2                    Chi Chi  ...  f153b465f       1.0\n",
              "2     2                     Sticky  ...  3c90f3f54       4.0\n",
              "3     1  Dannie & Kass [In Penang]  ...  e02abc8a3       5.0\n",
              "4     2                    Cuddles  ...  09f0df7d1       5.0\n",
              "\n",
              "[5 rows x 23 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "h2PColDpLzIj",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "763373c2-bead-42eb-c3ee-aa1743d9da3d"
      },
      "source": [
        "labels_breed.head()"
      ],
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>BreedID</th>\n",
              "      <th>Type</th>\n",
              "      <th>BreedName</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>Affenpinscher</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>Afghan Hound</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>Airedale Terrier</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>Akbash</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>Akita</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   BreedID  Type         BreedName\n",
              "0        1     1     Affenpinscher\n",
              "1        2     1      Afghan Hound\n",
              "2        3     1  Airedale Terrier\n",
              "3        4     1            Akbash\n",
              "4        5     1             Akita"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QKrB-ezZL4E1",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "1400ef23-3040-498c-f418-4433c057af35"
      },
      "source": [
        "labels_color.head()"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>41336</td>\n",
              "      <td>Johor</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>41325</td>\n",
              "      <td>Kedah</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>41367</td>\n",
              "      <td>Kelantan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>41401</td>\n",
              "      <td>Kuala Lumpur</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>41415</td>\n",
              "      <td>Labuan</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   StateID     StateName\n",
              "0    41336         Johor\n",
              "1    41325         Kedah\n",
              "2    41367      Kelantan\n",
              "3    41401  Kuala Lumpur\n",
              "4    41415        Labuan"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "u2bjF4lnL7HM",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "6b0052d3-a618-4700-f957-75b920761156"
      },
      "source": [
        "labels_state.head()"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>ColorID</th>\n",
              "      <th>ColorName</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>Black</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>Brown</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>Golden</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>Yellow</td>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>Cream</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   ColorID ColorName\n",
              "0        1     Black\n",
              "1        2     Brown\n",
              "2        3    Golden\n",
              "3        4    Yellow\n",
              "4        5     Cream"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bcNb47SmMnXr",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 561
        },
        "outputId": "07c1bfca-def0-4afa-e627-28de8bbff460"
      },
      "source": [
        "df_train_full.info()"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 14993 entries, 0 to 14992\n",
            "Data columns (total 27 columns):\n",
            "Unnamed: 0                    14993 non-null int64\n",
            "Type                          14993 non-null int64\n",
            "Name                          13736 non-null object\n",
            "Age                           14993 non-null int64\n",
            "Breed1                        14993 non-null int64\n",
            "Breed2                        14993 non-null int64\n",
            "Gender                        14993 non-null int64\n",
            "Color1                        14993 non-null int64\n",
            "Color2                        14993 non-null int64\n",
            "Color3                        14993 non-null int64\n",
            "MaturitySize                  14993 non-null int64\n",
            "FurLength                     14993 non-null int64\n",
            "Vaccinated                    14993 non-null int64\n",
            "Dewormed                      14993 non-null int64\n",
            "Sterilized                    14993 non-null int64\n",
            "Health                        14993 non-null int64\n",
            "Quantity                      14993 non-null int64\n",
            "Fee                           14993 non-null int64\n",
            "State                         14993 non-null int64\n",
            "RescuerID                     14993 non-null object\n",
            "VideoAmt                      14993 non-null int64\n",
            "Description                   14981 non-null object\n",
            "PetID                         14993 non-null object\n",
            "PhotoAmt                      14993 non-null float64\n",
            "AdoptionSpeed                 14993 non-null int64\n",
            "AdoptionSpeed_binary          14993 non-null int64\n",
            "AdoptionSpeed_four_classes    14993 non-null int64\n",
            "dtypes: float64(1), int64(22), object(4)\n",
            "memory usage: 3.1+ MB\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "NmDgYtX4NcLo",
        "colab_type": "text"
      },
      "source": [
        "# Notes"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "FCjNwPgENd6L",
        "colab_type": "text"
      },
      "source": [
        "Для датасета https://www.kaggle.com/c/petfinder-adoption-prediction выполнить предобработку признаков и построить оптимальные модели kNN и все типы классификаторов Байеса. Для перебора параметров можно использовать метод GridSearch"
      ]
    }
  ]
}