wine.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "wine.ipynb",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "XOAJBCD1NWcb",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "4a529933-b023-4d8a-c961-632810b3b221"
      },
      "source": [
        "import pathlib\n",
        "\n",
        "import matplotlib.pyplot as plt\n",
        "import pandas as pd\n",
        "import seaborn as sns\n",
        "import numpy as np\n",
        "import tensorflow as tf\n",
        "from tensorflow import keras\n",
        "from tensorflow.keras import layers\n",
        "\n",
        "print(tf.__version__)"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "2.3.0\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lcLqpLvwNaRA",
        "colab": {
          "resources": {
            "http://localhost:8080/nbextensions/google.colab/files.js": {
              "data": 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              "ok": true,
              "headers": [
                [
                  "content-type",
                  "application/javascript"
                ]
              ],
              "status": 200,
              "status_text": ""
            }
          },
          "base_uri": "https://localhost:8080/",
          "height": 90
        },
        "outputId": "355bfbbe-9a8f-4228-c887-7e6f4b881868"
      },
      "source": [
        "from google.colab import files\n",
        "\n",
        "uploaded = files.upload()\n",
        "\n",
        "for fn in uploaded.keys():\n",
        "  print('User uploaded file \"{name}\" with length {length} bytes'.format(\n",
        "      name=fn, length=len(uploaded[fn])))"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "\n",
              "     <input type=\"file\" id=\"files-fdb7dcfd-28d3-4df6-b012-80fc3a6823d8\" name=\"files[]\" multiple disabled\n",
              "        style=\"border:none\" />\n",
              "     <output id=\"result-fdb7dcfd-28d3-4df6-b012-80fc3a6823d8\">\n",
              "      Upload widget is only available when the cell has been executed in the\n",
              "      current browser session. Please rerun this cell to enable.\n",
              "      </output>\n",
              "      <script src=\"/nbextensions/google.colab/files.js\"></script> "
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Saving wine.data to wine.data\n",
            "User uploaded file \"wine.data\" with length 10782 bytes\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "n77ov_N9U9hw",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "0229a44b-de24-471e-8062-3db26a223a4d"
      },
      "source": [
        "!head {fn}\n",
        "dataset_path=fn"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "1,14.23,1.71,2.43,15.6,127,2.8,3.06,.28,2.29,5.64,1.04,3.92,1065\n",
            "1,13.2,1.78,2.14,11.2,100,2.65,2.76,.26,1.28,4.38,1.05,3.4,1050\n",
            "1,13.16,2.36,2.67,18.6,101,2.8,3.24,.3,2.81,5.68,1.03,3.17,1185\n",
            "1,14.37,1.95,2.5,16.8,113,3.85,3.49,.24,2.18,7.8,.86,3.45,1480\n",
            "1,13.24,2.59,2.87,21,118,2.8,2.69,.39,1.82,4.32,1.04,2.93,735\n",
            "1,14.2,1.76,2.45,15.2,112,3.27,3.39,.34,1.97,6.75,1.05,2.85,1450\n",
            "1,14.39,1.87,2.45,14.6,96,2.5,2.52,.3,1.98,5.25,1.02,3.58,1290\n",
            "1,14.06,2.15,2.61,17.6,121,2.6,2.51,.31,1.25,5.05,1.06,3.58,1295\n",
            "1,14.83,1.64,2.17,14,97,2.8,2.98,.29,1.98,5.2,1.08,2.85,1045\n",
            "1,13.86,1.35,2.27,16,98,2.98,3.15,.22,1.85,7.22,1.01,3.55,1045\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RYLfJLtMPOA3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 212
        },
        "outputId": "d28425e0-1a0f-45b5-c143-ff6bd70c24f5"
      },
      "source": [
        "column_names=['Type','Alcohol', 'Malic acid','Ash','Alcalinity of ash','Magnesium','Total phenols','Flavanoids','Nonflavanoid phenols','Proanthocyanins','Color intensity','Hue','OD280/OD315 of diluted wines','Proline']\n",
        "raw_dataset = pd.read_csv(dataset_path, names=column_names,\n",
        "                      na_values = \"?\", comment='\\t',\n",
        "                      sep=\",\", skipinitialspace=True)\n",
        "dataset = raw_dataset.copy()\n",
        "dataset.head()  "
      ],
      "execution_count": 4,
      "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>Type</th>\n",
              "      <th>Alcohol</th>\n",
              "      <th>Malic acid</th>\n",
              "      <th>Ash</th>\n",
              "      <th>Alcalinity of ash</th>\n",
              "      <th>Magnesium</th>\n",
              "      <th>Total phenols</th>\n",
              "      <th>Flavanoids</th>\n",
              "      <th>Nonflavanoid phenols</th>\n",
              "      <th>Proanthocyanins</th>\n",
              "      <th>Color intensity</th>\n",
              "      <th>Hue</th>\n",
              "      <th>OD280/OD315 of diluted wines</th>\n",
              "      <th>Proline</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>14.23</td>\n",
              "      <td>1.71</td>\n",
              "      <td>2.43</td>\n",
              "      <td>15.6</td>\n",
              "      <td>127</td>\n",
              "      <td>2.80</td>\n",
              "      <td>3.06</td>\n",
              "      <td>0.28</td>\n",
              "      <td>2.29</td>\n",
              "      <td>5.64</td>\n",
              "      <td>1.04</td>\n",
              "      <td>3.92</td>\n",
              "      <td>1065</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>13.20</td>\n",
              "      <td>1.78</td>\n",
              "      <td>2.14</td>\n",
              "      <td>11.2</td>\n",
              "      <td>100</td>\n",
              "      <td>2.65</td>\n",
              "      <td>2.76</td>\n",
              "      <td>0.26</td>\n",
              "      <td>1.28</td>\n",
              "      <td>4.38</td>\n",
              "      <td>1.05</td>\n",
              "      <td>3.40</td>\n",
              "      <td>1050</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1</td>\n",
              "      <td>13.16</td>\n",
              "      <td>2.36</td>\n",
              "      <td>2.67</td>\n",
              "      <td>18.6</td>\n",
              "      <td>101</td>\n",
              "      <td>2.80</td>\n",
              "      <td>3.24</td>\n",
              "      <td>0.30</td>\n",
              "      <td>2.81</td>\n",
              "      <td>5.68</td>\n",
              "      <td>1.03</td>\n",
              "      <td>3.17</td>\n",
              "      <td>1185</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1</td>\n",
              "      <td>14.37</td>\n",
              "      <td>1.95</td>\n",
              "      <td>2.50</td>\n",
              "      <td>16.8</td>\n",
              "      <td>113</td>\n",
              "      <td>3.85</td>\n",
              "      <td>3.49</td>\n",
              "      <td>0.24</td>\n",
              "      <td>2.18</td>\n",
              "      <td>7.80</td>\n",
              "      <td>0.86</td>\n",
              "      <td>3.45</td>\n",
              "      <td>1480</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1</td>\n",
              "      <td>13.24</td>\n",
              "      <td>2.59</td>\n",
              "      <td>2.87</td>\n",
              "      <td>21.0</td>\n",
              "      <td>118</td>\n",
              "      <td>2.80</td>\n",
              "      <td>2.69</td>\n",
              "      <td>0.39</td>\n",
              "      <td>1.82</td>\n",
              "      <td>4.32</td>\n",
              "      <td>1.04</td>\n",
              "      <td>2.93</td>\n",
              "      <td>735</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   Type  Alcohol  Malic acid  ...   Hue  OD280/OD315 of diluted wines  Proline\n",
              "0     1    14.23        1.71  ...  1.04                          3.92     1065\n",
              "1     1    13.20        1.78  ...  1.05                          3.40     1050\n",
              "2     1    13.16        2.36  ...  1.03                          3.17     1185\n",
              "3     1    14.37        1.95  ...  0.86                          3.45     1480\n",
              "4     1    13.24        2.59  ...  1.04                          2.93      735\n",
              "\n",
              "[5 rows x 14 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pEPituZUUl0U",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 212
        },
        "outputId": "575b5d34-bece-450b-ca97-bc1bac160787"
      },
      "source": [
        "dataset.tail()"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "      <th></th>\n",
              "      <th>Type</th>\n",
              "      <th>Alcohol</th>\n",
              "      <th>Malic acid</th>\n",
              "      <th>Ash</th>\n",
              "      <th>Alcalinity of ash</th>\n",
              "      <th>Magnesium</th>\n",
              "      <th>Total phenols</th>\n",
              "      <th>Flavanoids</th>\n",
              "      <th>Nonflavanoid phenols</th>\n",
              "      <th>Proanthocyanins</th>\n",
              "      <th>Color intensity</th>\n",
              "      <th>Hue</th>\n",
              "      <th>OD280/OD315 of diluted wines</th>\n",
              "      <th>Proline</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>173</th>\n",
              "      <td>3</td>\n",
              "      <td>13.71</td>\n",
              "      <td>5.65</td>\n",
              "      <td>2.45</td>\n",
              "      <td>20.5</td>\n",
              "      <td>95</td>\n",
              "      <td>1.68</td>\n",
              "      <td>0.61</td>\n",
              "      <td>0.52</td>\n",
              "      <td>1.06</td>\n",
              "      <td>7.7</td>\n",
              "      <td>0.64</td>\n",
              "      <td>1.74</td>\n",
              "      <td>740</td>\n",
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              "    <tr>\n",
              "      <th>174</th>\n",
              "      <td>3</td>\n",
              "      <td>13.40</td>\n",
              "      <td>3.91</td>\n",
              "      <td>2.48</td>\n",
              "      <td>23.0</td>\n",
              "      <td>102</td>\n",
              "      <td>1.80</td>\n",
              "      <td>0.75</td>\n",
              "      <td>0.43</td>\n",
              "      <td>1.41</td>\n",
              "      <td>7.3</td>\n",
              "      <td>0.70</td>\n",
              "      <td>1.56</td>\n",
              "      <td>750</td>\n",
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              "    <tr>\n",
              "      <th>175</th>\n",
              "      <td>3</td>\n",
              "      <td>13.27</td>\n",
              "      <td>4.28</td>\n",
              "      <td>2.26</td>\n",
              "      <td>20.0</td>\n",
              "      <td>120</td>\n",
              "      <td>1.59</td>\n",
              "      <td>0.69</td>\n",
              "      <td>0.43</td>\n",
              "      <td>1.35</td>\n",
              "      <td>10.2</td>\n",
              "      <td>0.59</td>\n",
              "      <td>1.56</td>\n",
              "      <td>835</td>\n",
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              "    <tr>\n",
              "      <th>176</th>\n",
              "      <td>3</td>\n",
              "      <td>13.17</td>\n",
              "      <td>2.59</td>\n",
              "      <td>2.37</td>\n",
              "      <td>20.0</td>\n",
              "      <td>120</td>\n",
              "      <td>1.65</td>\n",
              "      <td>0.68</td>\n",
              "      <td>0.53</td>\n",
              "      <td>1.46</td>\n",
              "      <td>9.3</td>\n",
              "      <td>0.60</td>\n",
              "      <td>1.62</td>\n",
              "      <td>840</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>177</th>\n",
              "      <td>3</td>\n",
              "      <td>14.13</td>\n",
              "      <td>4.10</td>\n",
              "      <td>2.74</td>\n",
              "      <td>24.5</td>\n",
              "      <td>96</td>\n",
              "      <td>2.05</td>\n",
              "      <td>0.76</td>\n",
              "      <td>0.56</td>\n",
              "      <td>1.35</td>\n",
              "      <td>9.2</td>\n",
              "      <td>0.61</td>\n",
              "      <td>1.60</td>\n",
              "      <td>560</td>\n",
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            "text/plain": [
              "     Type  Alcohol  Malic acid  ...   Hue  OD280/OD315 of diluted wines  Proline\n",
              "173     3    13.71        5.65  ...  0.64                          1.74      740\n",
              "174     3    13.40        3.91  ...  0.70                          1.56      750\n",
              "175     3    13.27        4.28  ...  0.59                          1.56      835\n",
              "176     3    13.17        2.59  ...  0.60                          1.62      840\n",
              "177     3    14.13        4.10  ...  0.61                          1.60      560\n",
              "\n",
              "[5 rows x 14 columns]"
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          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "40zPk7_zd3F-",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 269
        },
        "outputId": "6b8b2339-8e2e-4433-de34-246ab75be96c"
      },
      "source": [
        "dataset.isna().sum()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Type                            0\n",
              "Alcohol                         0\n",
              "Malic acid                      0\n",
              "Ash                             0\n",
              "Alcalinity of ash               0\n",
              "Magnesium                       0\n",
              "Total phenols                   0\n",
              "Flavanoids                      0\n",
              "Nonflavanoid phenols            0\n",
              "Proanthocyanins                 0\n",
              "Color intensity                 0\n",
              "Hue                             0\n",
              "OD280/OD315 of diluted wines    0\n",
              "Proline                         0\n",
              "dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "F5l4OrhrbTGn"
      },
      "source": [
        "oh=dataset.pop('Type')"
      ],
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BVpgxaoGaw0g"
      },
      "source": [
        "\n",
        "dataset['Type 1']=(oh==1)*1\n",
        "dataset['Type 2']=(oh==2)*1\n",
        "dataset['Type 3']=(oh==3)*1"
      ],
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oc0YOwSqcGF3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 418
        },
        "outputId": "f90fc68b-fb1d-4eb8-b894-bf2a9eb20732"
      },
      "source": [
        "dataset"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "  <thead>\n",
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              "      <th></th>\n",
              "      <th>Alcohol</th>\n",
              "      <th>Malic acid</th>\n",
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              "      <th>Type 1</th>\n",
              "      <th>Type 2</th>\n",
              "      <th>Type 3</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>14.23</td>\n",
              "      <td>1.71</td>\n",
              "      <td>2.43</td>\n",
              "      <td>15.6</td>\n",
              "      <td>127</td>\n",
              "      <td>2.80</td>\n",
              "      <td>3.06</td>\n",
              "      <td>0.28</td>\n",
              "      <td>2.29</td>\n",
              "      <td>5.64</td>\n",
              "      <td>1.04</td>\n",
              "      <td>3.92</td>\n",
              "      <td>1065</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>13.20</td>\n",
              "      <td>1.78</td>\n",
              "      <td>2.14</td>\n",
              "      <td>11.2</td>\n",
              "      <td>100</td>\n",
              "      <td>2.65</td>\n",
              "      <td>2.76</td>\n",
              "      <td>0.26</td>\n",
              "      <td>1.28</td>\n",
              "      <td>4.38</td>\n",
              "      <td>1.05</td>\n",
              "      <td>3.40</td>\n",
              "      <td>1050</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>13.16</td>\n",
              "      <td>2.36</td>\n",
              "      <td>2.67</td>\n",
              "      <td>18.6</td>\n",
              "      <td>101</td>\n",
              "      <td>2.80</td>\n",
              "      <td>3.24</td>\n",
              "      <td>0.30</td>\n",
              "      <td>2.81</td>\n",
              "      <td>5.68</td>\n",
              "      <td>1.03</td>\n",
              "      <td>3.17</td>\n",
              "      <td>1185</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>14.37</td>\n",
              "      <td>1.95</td>\n",
              "      <td>2.50</td>\n",
              "      <td>16.8</td>\n",
              "      <td>113</td>\n",
              "      <td>3.85</td>\n",
              "      <td>3.49</td>\n",
              "      <td>0.24</td>\n",
              "      <td>2.18</td>\n",
              "      <td>7.80</td>\n",
              "      <td>0.86</td>\n",
              "      <td>3.45</td>\n",
              "      <td>1480</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>13.24</td>\n",
              "      <td>2.59</td>\n",
              "      <td>2.87</td>\n",
              "      <td>21.0</td>\n",
              "      <td>118</td>\n",
              "      <td>2.80</td>\n",
              "      <td>2.69</td>\n",
              "      <td>0.39</td>\n",
              "      <td>1.82</td>\n",
              "      <td>4.32</td>\n",
              "      <td>1.04</td>\n",
              "      <td>2.93</td>\n",
              "      <td>735</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "    <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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>173</th>\n",
              "      <td>13.71</td>\n",
              "      <td>5.65</td>\n",
              "      <td>2.45</td>\n",
              "      <td>20.5</td>\n",
              "      <td>95</td>\n",
              "      <td>1.68</td>\n",
              "      <td>0.61</td>\n",
              "      <td>0.52</td>\n",
              "      <td>1.06</td>\n",
              "      <td>7.70</td>\n",
              "      <td>0.64</td>\n",
              "      <td>1.74</td>\n",
              "      <td>740</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
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              "    <tr>\n",
              "      <th>174</th>\n",
              "      <td>13.40</td>\n",
              "      <td>3.91</td>\n",
              "      <td>2.48</td>\n",
              "      <td>23.0</td>\n",
              "      <td>102</td>\n",
              "      <td>1.80</td>\n",
              "      <td>0.75</td>\n",
              "      <td>0.43</td>\n",
              "      <td>1.41</td>\n",
              "      <td>7.30</td>\n",
              "      <td>0.70</td>\n",
              "      <td>1.56</td>\n",
              "      <td>750</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>175</th>\n",
              "      <td>13.27</td>\n",
              "      <td>4.28</td>\n",
              "      <td>2.26</td>\n",
              "      <td>20.0</td>\n",
              "      <td>120</td>\n",
              "      <td>1.59</td>\n",
              "      <td>0.69</td>\n",
              "      <td>0.43</td>\n",
              "      <td>1.35</td>\n",
              "      <td>10.20</td>\n",
              "      <td>0.59</td>\n",
              "      <td>1.56</td>\n",
              "      <td>835</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>176</th>\n",
              "      <td>13.17</td>\n",
              "      <td>2.59</td>\n",
              "      <td>2.37</td>\n",
              "      <td>20.0</td>\n",
              "      <td>120</td>\n",
              "      <td>1.65</td>\n",
              "      <td>0.68</td>\n",
              "      <td>0.53</td>\n",
              "      <td>1.46</td>\n",
              "      <td>9.30</td>\n",
              "      <td>0.60</td>\n",
              "      <td>1.62</td>\n",
              "      <td>840</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>177</th>\n",
              "      <td>14.13</td>\n",
              "      <td>4.10</td>\n",
              "      <td>2.74</td>\n",
              "      <td>24.5</td>\n",
              "      <td>96</td>\n",
              "      <td>2.05</td>\n",
              "      <td>0.76</td>\n",
              "      <td>0.56</td>\n",
              "      <td>1.35</td>\n",
              "      <td>9.20</td>\n",
              "      <td>0.61</td>\n",
              "      <td>1.60</td>\n",
              "      <td>560</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>178 rows × 16 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "     Alcohol  Malic acid   Ash  ...  Type 1  Type 2  Type 3\n",
              "0      14.23        1.71  2.43  ...       1       0       0\n",
              "1      13.20        1.78  2.14  ...       1       0       0\n",
              "2      13.16        2.36  2.67  ...       1       0       0\n",
              "3      14.37        1.95  2.50  ...       1       0       0\n",
              "4      13.24        2.59  2.87  ...       1       0       0\n",
              "..       ...         ...   ...  ...     ...     ...     ...\n",
              "173    13.71        5.65  2.45  ...       0       0       1\n",
              "174    13.40        3.91  2.48  ...       0       0       1\n",
              "175    13.27        4.28  2.26  ...       0       0       1\n",
              "176    13.17        2.59  2.37  ...       0       0       1\n",
              "177    14.13        4.10  2.74  ...       0       0       1\n",
              "\n",
              "[178 rows x 16 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Qocs0uw9d98f"
      },
      "source": [
        "train_dataset = dataset.sample(frac=0.8,random_state=0)\n",
        "test_dataset = dataset.drop(train_dataset.index)"
      ],
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ojKFMfG4k3pQ",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 418
        },
        "outputId": "4d0ad10b-0aa6-479c-812f-a244df31607b"
      },
      "source": [
        "train_dataset"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Alcohol</th>\n",
              "      <th>Malic acid</th>\n",
              "      <th>Ash</th>\n",
              "      <th>Alcalinity of ash</th>\n",
              "      <th>Magnesium</th>\n",
              "      <th>Total phenols</th>\n",
              "      <th>Flavanoids</th>\n",
              "      <th>Nonflavanoid phenols</th>\n",
              "      <th>Proanthocyanins</th>\n",
              "      <th>Color intensity</th>\n",
              "      <th>Hue</th>\n",
              "      <th>OD280/OD315 of diluted wines</th>\n",
              "      <th>Proline</th>\n",
              "      <th>Type 1</th>\n",
              "      <th>Type 2</th>\n",
              "      <th>Type 3</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>54</th>\n",
              "      <td>13.74</td>\n",
              "      <td>1.67</td>\n",
              "      <td>2.25</td>\n",
              "      <td>16.4</td>\n",
              "      <td>118</td>\n",
              "      <td>2.60</td>\n",
              "      <td>2.90</td>\n",
              "      <td>0.21</td>\n",
              "      <td>1.62</td>\n",
              "      <td>5.85</td>\n",
              "      <td>0.92</td>\n",
              "      <td>3.20</td>\n",
              "      <td>1060</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>151</th>\n",
              "      <td>12.79</td>\n",
              "      <td>2.67</td>\n",
              "      <td>2.48</td>\n",
              "      <td>22.0</td>\n",
              "      <td>112</td>\n",
              "      <td>1.48</td>\n",
              "      <td>1.36</td>\n",
              "      <td>0.24</td>\n",
              "      <td>1.26</td>\n",
              "      <td>10.80</td>\n",
              "      <td>0.48</td>\n",
              "      <td>1.47</td>\n",
              "      <td>480</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>63</th>\n",
              "      <td>12.37</td>\n",
              "      <td>1.13</td>\n",
              "      <td>2.16</td>\n",
              "      <td>19.0</td>\n",
              "      <td>87</td>\n",
              "      <td>3.50</td>\n",
              "      <td>3.10</td>\n",
              "      <td>0.19</td>\n",
              "      <td>1.87</td>\n",
              "      <td>4.45</td>\n",
              "      <td>1.22</td>\n",
              "      <td>2.87</td>\n",
              "      <td>420</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>55</th>\n",
              "      <td>13.56</td>\n",
              "      <td>1.73</td>\n",
              "      <td>2.46</td>\n",
              "      <td>20.5</td>\n",
              "      <td>116</td>\n",
              "      <td>2.96</td>\n",
              "      <td>2.78</td>\n",
              "      <td>0.20</td>\n",
              "      <td>2.45</td>\n",
              "      <td>6.25</td>\n",
              "      <td>0.98</td>\n",
              "      <td>3.03</td>\n",
              "      <td>1120</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>123</th>\n",
              "      <td>13.05</td>\n",
              "      <td>5.80</td>\n",
              "      <td>2.13</td>\n",
              "      <td>21.5</td>\n",
              "      <td>86</td>\n",
              "      <td>2.62</td>\n",
              "      <td>2.65</td>\n",
              "      <td>0.30</td>\n",
              "      <td>2.01</td>\n",
              "      <td>2.60</td>\n",
              "      <td>0.73</td>\n",
              "      <td>3.10</td>\n",
              "      <td>380</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>53</th>\n",
              "      <td>13.77</td>\n",
              "      <td>1.90</td>\n",
              "      <td>2.68</td>\n",
              "      <td>17.1</td>\n",
              "      <td>115</td>\n",
              "      <td>3.00</td>\n",
              "      <td>2.79</td>\n",
              "      <td>0.39</td>\n",
              "      <td>1.68</td>\n",
              "      <td>6.30</td>\n",
              "      <td>1.13</td>\n",
              "      <td>2.93</td>\n",
              "      <td>1375</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>139</th>\n",
              "      <td>12.84</td>\n",
              "      <td>2.96</td>\n",
              "      <td>2.61</td>\n",
              "      <td>24.0</td>\n",
              "      <td>101</td>\n",
              "      <td>2.32</td>\n",
              "      <td>0.60</td>\n",
              "      <td>0.53</td>\n",
              "      <td>0.81</td>\n",
              "      <td>4.92</td>\n",
              "      <td>0.89</td>\n",
              "      <td>2.15</td>\n",
              "      <td>590</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>128</th>\n",
              "      <td>12.37</td>\n",
              "      <td>1.63</td>\n",
              "      <td>2.30</td>\n",
              "      <td>24.5</td>\n",
              "      <td>88</td>\n",
              "      <td>2.22</td>\n",
              "      <td>2.45</td>\n",
              "      <td>0.40</td>\n",
              "      <td>1.90</td>\n",
              "      <td>2.12</td>\n",
              "      <td>0.89</td>\n",
              "      <td>2.78</td>\n",
              "      <td>342</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>34</th>\n",
              "      <td>13.51</td>\n",
              "      <td>1.80</td>\n",
              "      <td>2.65</td>\n",
              "      <td>19.0</td>\n",
              "      <td>110</td>\n",
              "      <td>2.35</td>\n",
              "      <td>2.53</td>\n",
              "      <td>0.29</td>\n",
              "      <td>1.54</td>\n",
              "      <td>4.20</td>\n",
              "      <td>1.10</td>\n",
              "      <td>2.87</td>\n",
              "      <td>1095</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>13.87</td>\n",
              "      <td>1.90</td>\n",
              "      <td>2.80</td>\n",
              "      <td>19.4</td>\n",
              "      <td>107</td>\n",
              "      <td>2.95</td>\n",
              "      <td>2.97</td>\n",
              "      <td>0.37</td>\n",
              "      <td>1.76</td>\n",
              "      <td>4.50</td>\n",
              "      <td>1.25</td>\n",
              "      <td>3.40</td>\n",
              "      <td>915</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>142 rows × 16 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "     Alcohol  Malic acid   Ash  ...  Type 1  Type 2  Type 3\n",
              "54     13.74        1.67  2.25  ...       1       0       0\n",
              "151    12.79        2.67  2.48  ...       0       0       1\n",
              "63     12.37        1.13  2.16  ...       0       1       0\n",
              "55     13.56        1.73  2.46  ...       1       0       0\n",
              "123    13.05        5.80  2.13  ...       0       1       0\n",
              "..       ...         ...   ...  ...     ...     ...     ...\n",
              "53     13.77        1.90  2.68  ...       1       0       0\n",
              "139    12.84        2.96  2.61  ...       0       0       1\n",
              "128    12.37        1.63  2.30  ...       0       1       0\n",
              "34     13.51        1.80  2.65  ...       1       0       0\n",
              "28     13.87        1.90  2.80  ...       1       0       0\n",
              "\n",
              "[142 rows x 16 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MMDgeYQSrhg0",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 338
        },
        "outputId": "5309a94b-9425-40cf-c079-93780a42a194"
      },
      "source": [
        "train_stats = train_dataset.describe()\n",
        "train_stats"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Alcohol</th>\n",
              "      <th>Malic acid</th>\n",
              "      <th>Ash</th>\n",
              "      <th>Alcalinity of ash</th>\n",
              "      <th>Magnesium</th>\n",
              "      <th>Total phenols</th>\n",
              "      <th>Flavanoids</th>\n",
              "      <th>Nonflavanoid phenols</th>\n",
              "      <th>Proanthocyanins</th>\n",
              "      <th>Color intensity</th>\n",
              "      <th>Hue</th>\n",
              "      <th>OD280/OD315 of diluted wines</th>\n",
              "      <th>Proline</th>\n",
              "      <th>Type 1</th>\n",
              "      <th>Type 2</th>\n",
              "      <th>Type 3</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>142.000000</td>\n",
              "      <td>142.000000</td>\n",
              "      <td>142.000000</td>\n",
              "      <td>142.000000</td>\n",
              "      <td>142.000000</td>\n",
              "      <td>142.000000</td>\n",
              "      <td>142.000000</td>\n",
              "      <td>142.000000</td>\n",
              "      <td>142.000000</td>\n",
              "      <td>142.000000</td>\n",
              "      <td>142.000000</td>\n",
              "      <td>142.000000</td>\n",
              "      <td>142.000000</td>\n",
              "      <td>142.000000</td>\n",
              "      <td>142.000000</td>\n",
              "      <td>142.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>13.024507</td>\n",
              "      <td>2.302113</td>\n",
              "      <td>2.347676</td>\n",
              "      <td>19.154225</td>\n",
              "      <td>100.183099</td>\n",
              "      <td>2.321479</td>\n",
              "      <td>2.065986</td>\n",
              "      <td>0.357887</td>\n",
              "      <td>1.615211</td>\n",
              "      <td>5.045141</td>\n",
              "      <td>0.957042</td>\n",
              "      <td>2.614718</td>\n",
              "      <td>761.739437</td>\n",
              "      <td>0.345070</td>\n",
              "      <td>0.394366</td>\n",
              "      <td>0.260563</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>0.806539</td>\n",
              "      <td>1.135063</td>\n",
              "      <td>0.271937</td>\n",
              "      <td>3.206589</td>\n",
              "      <td>14.659066</td>\n",
              "      <td>0.641318</td>\n",
              "      <td>1.016488</td>\n",
              "      <td>0.125708</td>\n",
              "      <td>0.590732</td>\n",
              "      <td>2.256657</td>\n",
              "      <td>0.218891</td>\n",
              "      <td>0.717042</td>\n",
              "      <td>326.151787</td>\n",
              "      <td>0.477074</td>\n",
              "      <td>0.490444</td>\n",
              "      <td>0.440496</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>11.410000</td>\n",
              "      <td>0.740000</td>\n",
              "      <td>1.360000</td>\n",
              "      <td>10.600000</td>\n",
              "      <td>70.000000</td>\n",
              "      <td>0.980000</td>\n",
              "      <td>0.340000</td>\n",
              "      <td>0.130000</td>\n",
              "      <td>0.410000</td>\n",
              "      <td>1.280000</td>\n",
              "      <td>0.480000</td>\n",
              "      <td>1.270000</td>\n",
              "      <td>278.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>12.370000</td>\n",
              "      <td>1.540000</td>\n",
              "      <td>2.200000</td>\n",
              "      <td>17.000000</td>\n",
              "      <td>89.000000</td>\n",
              "      <td>1.742500</td>\n",
              "      <td>1.227500</td>\n",
              "      <td>0.270000</td>\n",
              "      <td>1.265000</td>\n",
              "      <td>3.277500</td>\n",
              "      <td>0.790000</td>\n",
              "      <td>1.970000</td>\n",
              "      <td>504.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>13.050000</td>\n",
              "      <td>1.845000</td>\n",
              "      <td>2.350000</td>\n",
              "      <td>19.000000</td>\n",
              "      <td>98.000000</td>\n",
              "      <td>2.410000</td>\n",
              "      <td>2.180000</td>\n",
              "      <td>0.320000</td>\n",
              "      <td>1.560000</td>\n",
              "      <td>4.900000</td>\n",
              "      <td>0.970000</td>\n",
              "      <td>2.780000</td>\n",
              "      <td>679.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>13.705000</td>\n",
              "      <td>2.927500</td>\n",
              "      <td>2.540000</td>\n",
              "      <td>21.000000</td>\n",
              "      <td>107.000000</td>\n",
              "      <td>2.800000</td>\n",
              "      <td>2.907500</td>\n",
              "      <td>0.430000</td>\n",
              "      <td>1.957500</td>\n",
              "      <td>6.000000</td>\n",
              "      <td>1.120000</td>\n",
              "      <td>3.170000</td>\n",
              "      <td>1035.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>14.830000</td>\n",
              "      <td>5.800000</td>\n",
              "      <td>3.230000</td>\n",
              "      <td>30.000000</td>\n",
              "      <td>162.000000</td>\n",
              "      <td>3.880000</td>\n",
              "      <td>5.080000</td>\n",
              "      <td>0.660000</td>\n",
              "      <td>3.580000</td>\n",
              "      <td>13.000000</td>\n",
              "      <td>1.450000</td>\n",
              "      <td>4.000000</td>\n",
              "      <td>1680.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "          Alcohol  Malic acid         Ash  ...      Type 1      Type 2      Type 3\n",
              "count  142.000000  142.000000  142.000000  ...  142.000000  142.000000  142.000000\n",
              "mean    13.024507    2.302113    2.347676  ...    0.345070    0.394366    0.260563\n",
              "std      0.806539    1.135063    0.271937  ...    0.477074    0.490444    0.440496\n",
              "min     11.410000    0.740000    1.360000  ...    0.000000    0.000000    0.000000\n",
              "25%     12.370000    1.540000    2.200000  ...    0.000000    0.000000    0.000000\n",
              "50%     13.050000    1.845000    2.350000  ...    0.000000    0.000000    0.000000\n",
              "75%     13.705000    2.927500    2.540000  ...    1.000000    1.000000    1.000000\n",
              "max     14.830000    5.800000    3.230000  ...    1.000000    1.000000    1.000000\n",
              "\n",
              "[8 rows x 16 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "C1tspFGnrlg-"
      },
      "source": [
        "train_labels=train_dataset[['Type 1','Type 2','Type 3']]"
      ],
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kPD1cIZwX6n5"
      },
      "source": [
        "test_labels=test_dataset[['Type 1','Type 2','Type 3']]"
      ],
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "aatcv5_UX9-y"
      },
      "source": [
        "def build_model():\n",
        "  model = keras.Sequential([\n",
        "    layers.Dense(64, activation=tf.nn.relu, input_shape=[len(train_dataset.keys())]),\n",
        "    layers.Dense(64, activation=tf.nn.relu),\n",
        "    layers.Dense(3,  activation=tf.nn.softmax)\n",
        "  ])\n",
        "\n",
        "\n",
        "  model.compile(loss='categorical_crossentropy', \n",
        "                      optimizer='adam', \n",
        "                      metrics=['accuracy'])\n",
        "  return model"
      ],
      "execution_count": 14,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TowHRxl5t6WP"
      },
      "source": [
        "model=build_model()"
      ],
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BkFMtGXcF7mG",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "83f8027e-d471-4567-d179-c9e524248a87"
      },
      "source": [
        "model.summary()"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Model: \"sequential\"\n",
            "_________________________________________________________________\n",
            "Layer (type)                 Output Shape              Param #   \n",
            "=================================================================\n",
            "dense (Dense)                (None, 64)                1088      \n",
            "_________________________________________________________________\n",
            "dense_1 (Dense)              (None, 64)                4160      \n",
            "_________________________________________________________________\n",
            "dense_2 (Dense)              (None, 3)                 195       \n",
            "=================================================================\n",
            "Total params: 5,443\n",
            "Trainable params: 5,443\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-6PRkifMPqZD"
      },
      "source": [
        "class PrintDot(keras.callbacks.Callback):\n",
        "  def on_epoch_end(self, epoch, logs):\n",
        "    if epoch % 100 == 0: print('')\n",
        "    print('.', end='')"
      ],
      "execution_count": 17,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 418
        },
        "id": "gVURLCoxVI3D",
        "outputId": "c68f4021-a9d3-4f04-b482-ed8d686ad844"
      },
      "source": [
        "train_dataset.pop('Type 1')\n",
        "train_dataset.pop('Type 2')\n",
        "train_dataset.pop('Type 3')\n",
        "test_dataset.pop('Type 1')\n",
        "test_dataset.pop('Type 2')\n",
        "test_dataset.pop('Type 3')"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
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              "    }\n",
              "\n",
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              "    }\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>Alcohol</th>\n",
              "      <th>Malic acid</th>\n",
              "      <th>Ash</th>\n",
              "      <th>Alcalinity of ash</th>\n",
              "      <th>Magnesium</th>\n",
              "      <th>Total phenols</th>\n",
              "      <th>Flavanoids</th>\n",
              "      <th>Nonflavanoid phenols</th>\n",
              "      <th>Proanthocyanins</th>\n",
              "      <th>Color intensity</th>\n",
              "      <th>Hue</th>\n",
              "      <th>OD280/OD315 of diluted wines</th>\n",
              "      <th>Proline</th>\n",
              "      <th>Type 1</th>\n",
              "      <th>Type 2</th>\n",
              "      <th>Type 3</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>54</th>\n",
              "      <td>13.74</td>\n",
              "      <td>1.67</td>\n",
              "      <td>2.25</td>\n",
              "      <td>16.4</td>\n",
              "      <td>118</td>\n",
              "      <td>2.60</td>\n",
              "      <td>2.90</td>\n",
              "      <td>0.21</td>\n",
              "      <td>1.62</td>\n",
              "      <td>5.85</td>\n",
              "      <td>0.92</td>\n",
              "      <td>3.20</td>\n",
              "      <td>1060</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>151</th>\n",
              "      <td>12.79</td>\n",
              "      <td>2.67</td>\n",
              "      <td>2.48</td>\n",
              "      <td>22.0</td>\n",
              "      <td>112</td>\n",
              "      <td>1.48</td>\n",
              "      <td>1.36</td>\n",
              "      <td>0.24</td>\n",
              "      <td>1.26</td>\n",
              "      <td>10.80</td>\n",
              "      <td>0.48</td>\n",
              "      <td>1.47</td>\n",
              "      <td>480</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>63</th>\n",
              "      <td>12.37</td>\n",
              "      <td>1.13</td>\n",
              "      <td>2.16</td>\n",
              "      <td>19.0</td>\n",
              "      <td>87</td>\n",
              "      <td>3.50</td>\n",
              "      <td>3.10</td>\n",
              "      <td>0.19</td>\n",
              "      <td>1.87</td>\n",
              "      <td>4.45</td>\n",
              "      <td>1.22</td>\n",
              "      <td>2.87</td>\n",
              "      <td>420</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>55</th>\n",
              "      <td>13.56</td>\n",
              "      <td>1.73</td>\n",
              "      <td>2.46</td>\n",
              "      <td>20.5</td>\n",
              "      <td>116</td>\n",
              "      <td>2.96</td>\n",
              "      <td>2.78</td>\n",
              "      <td>0.20</td>\n",
              "      <td>2.45</td>\n",
              "      <td>6.25</td>\n",
              "      <td>0.98</td>\n",
              "      <td>3.03</td>\n",
              "      <td>1120</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>123</th>\n",
              "      <td>13.05</td>\n",
              "      <td>5.80</td>\n",
              "      <td>2.13</td>\n",
              "      <td>21.5</td>\n",
              "      <td>86</td>\n",
              "      <td>2.62</td>\n",
              "      <td>2.65</td>\n",
              "      <td>0.30</td>\n",
              "      <td>2.01</td>\n",
              "      <td>2.60</td>\n",
              "      <td>0.73</td>\n",
              "      <td>3.10</td>\n",
              "      <td>380</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>53</th>\n",
              "      <td>13.77</td>\n",
              "      <td>1.90</td>\n",
              "      <td>2.68</td>\n",
              "      <td>17.1</td>\n",
              "      <td>115</td>\n",
              "      <td>3.00</td>\n",
              "      <td>2.79</td>\n",
              "      <td>0.39</td>\n",
              "      <td>1.68</td>\n",
              "      <td>6.30</td>\n",
              "      <td>1.13</td>\n",
              "      <td>2.93</td>\n",
              "      <td>1375</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>139</th>\n",
              "      <td>12.84</td>\n",
              "      <td>2.96</td>\n",
              "      <td>2.61</td>\n",
              "      <td>24.0</td>\n",
              "      <td>101</td>\n",
              "      <td>2.32</td>\n",
              "      <td>0.60</td>\n",
              "      <td>0.53</td>\n",
              "      <td>0.81</td>\n",
              "      <td>4.92</td>\n",
              "      <td>0.89</td>\n",
              "      <td>2.15</td>\n",
              "      <td>590</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>128</th>\n",
              "      <td>12.37</td>\n",
              "      <td>1.63</td>\n",
              "      <td>2.30</td>\n",
              "      <td>24.5</td>\n",
              "      <td>88</td>\n",
              "      <td>2.22</td>\n",
              "      <td>2.45</td>\n",
              "      <td>0.40</td>\n",
              "      <td>1.90</td>\n",
              "      <td>2.12</td>\n",
              "      <td>0.89</td>\n",
              "      <td>2.78</td>\n",
              "      <td>342</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>34</th>\n",
              "      <td>13.51</td>\n",
              "      <td>1.80</td>\n",
              "      <td>2.65</td>\n",
              "      <td>19.0</td>\n",
              "      <td>110</td>\n",
              "      <td>2.35</td>\n",
              "      <td>2.53</td>\n",
              "      <td>0.29</td>\n",
              "      <td>1.54</td>\n",
              "      <td>4.20</td>\n",
              "      <td>1.10</td>\n",
              "      <td>2.87</td>\n",
              "      <td>1095</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>13.87</td>\n",
              "      <td>1.90</td>\n",
              "      <td>2.80</td>\n",
              "      <td>19.4</td>\n",
              "      <td>107</td>\n",
              "      <td>2.95</td>\n",
              "      <td>2.97</td>\n",
              "      <td>0.37</td>\n",
              "      <td>1.76</td>\n",
              "      <td>4.50</td>\n",
              "      <td>1.25</td>\n",
              "      <td>3.40</td>\n",
              "      <td>915</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>142 rows × 16 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "     Alcohol  Malic acid   Ash  ...  Type 1  Type 2  Type 3\n",
              "54     13.74        1.67  2.25  ...       1       0       0\n",
              "151    12.79        2.67  2.48  ...       0       0       1\n",
              "63     12.37        1.13  2.16  ...       0       1       0\n",
              "55     13.56        1.73  2.46  ...       1       0       0\n",
              "123    13.05        5.80  2.13  ...       0       1       0\n",
              "..       ...         ...   ...  ...     ...     ...     ...\n",
              "53     13.77        1.90  2.68  ...       1       0       0\n",
              "139    12.84        2.96  2.61  ...       0       0       1\n",
              "128    12.37        1.63  2.30  ...       0       1       0\n",
              "34     13.51        1.80  2.65  ...       1       0       0\n",
              "28     13.87        1.90  2.80  ...       1       0       0\n",
              "\n",
              "[142 rows x 16 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "iVNxQJ6-Pes4",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "6da06de1-9bb4-4ba5-99a1-27d6696557f9"
      },
      "source": [
        "\n",
        "history = model.fit(\n",
        " train_dataset, train_labels,\n",
        "  epochs=100, validation_split = 0.2, verbose=0\n",
        "  ,callbacks=[PrintDot()])"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "\n",
            "...................................................................................................."
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rOjHfCKuPsoM",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 195
        },
        "outputId": "f62b47bd-4002-47c3-d3d5-22ce96cc45cf"
      },
      "source": [
        "hist = pd.DataFrame(history.history)\n",
        "hist['epoch'] = history.epoch\n",
        "hist.tail()"
      ],
      "execution_count": 20,
      "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>loss</th>\n",
              "      <th>accuracy</th>\n",
              "      <th>val_loss</th>\n",
              "      <th>val_accuracy</th>\n",
              "      <th>epoch</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>95</th>\n",
              "      <td>0.354624</td>\n",
              "      <td>0.893805</td>\n",
              "      <td>0.084689</td>\n",
              "      <td>0.965517</td>\n",
              "      <td>95</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>96</th>\n",
              "      <td>0.371951</td>\n",
              "      <td>0.911504</td>\n",
              "      <td>0.115297</td>\n",
              "      <td>0.965517</td>\n",
              "      <td>96</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>97</th>\n",
              "      <td>0.336019</td>\n",
              "      <td>0.858407</td>\n",
              "      <td>0.111262</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>97</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>98</th>\n",
              "      <td>0.451561</td>\n",
              "      <td>0.858407</td>\n",
              "      <td>0.215153</td>\n",
              "      <td>0.965517</td>\n",
              "      <td>98</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>99</th>\n",
              "      <td>0.271764</td>\n",
              "      <td>0.955752</td>\n",
              "      <td>0.257871</td>\n",
              "      <td>0.862069</td>\n",
              "      <td>99</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "        loss  accuracy  val_loss  val_accuracy  epoch\n",
              "95  0.354624  0.893805  0.084689      0.965517     95\n",
              "96  0.371951  0.911504  0.115297      0.965517     96\n",
              "97  0.336019  0.858407  0.111262      1.000000     97\n",
              "98  0.451561  0.858407  0.215153      0.965517     98\n",
              "99  0.271764  0.955752  0.257871      0.862069     99"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jPhpNDUJPzp8",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "fe20c387-9227-4773-dbbe-ec05bb487e12"
      },
      "source": [
        "early_stop = keras.callbacks.EarlyStopping(monitor='val_loss', patience=10)\n",
        "\n",
        "history = model.fit(\n",
        " train_dataset, train_labels,\n",
        "  epochs=100, validation_split = 0.2, verbose=0\n",
        "  ,callbacks=[early_stop,PrintDot()])"
      ],
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "\n",
            "..............................."
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "i3Ih-PJhRHUC",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "2d0020fc-5f41-48df-f5cc-cdd7782c9928"
      },
      "source": [
        "test_loss, test_acc = model.evaluate(test_dataset, test_labels)\n"
      ],
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "2/2 [==============================] - 0s 3ms/step - loss: 0.2835 - accuracy: 0.8889\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SVXv7GA4QASS"
      },
      "source": [
        "predictions=model.predict(test_dataset)"
      ],
      "execution_count": 23,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "a01Y7acqQzo4",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "72561c05-9058-48b5-cb7c-7ba05347580d"
      },
      "source": [
        "predictions[0]"
      ],
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([0.99682486, 0.00153623, 0.00163896], dtype=float32)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6rXmeB3pQ4BL"
      },
      "source": [
        "test_labels=np.array(test_labels)"
      ],
      "execution_count": 30,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Aust7T73SIuT",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "68172f39-0e0b-41b2-9b66-5f93bf78bd9c"
      },
      "source": [
        "test_labels[0]"
      ],
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([1, 0, 0])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RLdgJ-fFQwo2",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "558c1578-5dd8-479a-94d1-a9e2e1382681"
      },
      "source": [
        "np.argmax(predictions[0])"
      ],
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 31
        }
      ]
    }
  ]
}