Power_Transformation_example.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Power Transformation example.ipynb",
      "provenance": [],
      "authorship_tag": "ABX9TyNdL7PkiYSA6TDCcSR7r/Iy"
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "eKLZrzOlsN0X"
      },
      "source": [
        "from sklearn.datasets import load_breast_cancer"
      ],
      "execution_count": 78,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DX-SWhGitHXW"
      },
      "source": [
        "import pandas as pd"
      ],
      "execution_count": 79,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "h87hzm8-sRf0"
      },
      "source": [
        "from sklearn.preprocessing import StandardScaler\n",
        "from sklearn.neighbors import KNeighborsClassifier\n",
        "from sklearn.pipeline import Pipeline\n",
        "from sklearn.metrics import roc_auc_score,balanced_accuracy_score\n",
        "from sklearn.model_selection import GridSearchCV, train_test_split\n",
        "from sklearn.preprocessing import PowerTransformer\n",
        "import matplotlib.pyplot as plt"
      ],
      "execution_count": 80,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vKtNmRqPsWFK"
      },
      "source": [
        "d = load_breast_cancer()\n",
        "\n",
        "df = pd.DataFrame(d['data'],columns=d['feature_names']).iloc[:,0:6]\n"
      ],
      "execution_count": 92,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "M3rimRlhttWW"
      },
      "source": [
        "plt.rc('font', size=12) \n",
        "plt.rcParams['figure.figsize'] = [10, 10]"
      ],
      "execution_count": 93,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "id": "9YUKmT7BvmB5",
        "outputId": "f73f0177-d18a-455d-dc7e-ad73ad1e54fb"
      },
      "source": [
        "df"
      ],
      "execution_count": 94,
      "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>mean radius</th>\n",
              "      <th>mean texture</th>\n",
              "      <th>mean perimeter</th>\n",
              "      <th>mean area</th>\n",
              "      <th>mean smoothness</th>\n",
              "      <th>mean compactness</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>17.99</td>\n",
              "      <td>10.38</td>\n",
              "      <td>122.80</td>\n",
              "      <td>1001.0</td>\n",
              "      <td>0.11840</td>\n",
              "      <td>0.27760</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>20.57</td>\n",
              "      <td>17.77</td>\n",
              "      <td>132.90</td>\n",
              "      <td>1326.0</td>\n",
              "      <td>0.08474</td>\n",
              "      <td>0.07864</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>19.69</td>\n",
              "      <td>21.25</td>\n",
              "      <td>130.00</td>\n",
              "      <td>1203.0</td>\n",
              "      <td>0.10960</td>\n",
              "      <td>0.15990</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>11.42</td>\n",
              "      <td>20.38</td>\n",
              "      <td>77.58</td>\n",
              "      <td>386.1</td>\n",
              "      <td>0.14250</td>\n",
              "      <td>0.28390</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>20.29</td>\n",
              "      <td>14.34</td>\n",
              "      <td>135.10</td>\n",
              "      <td>1297.0</td>\n",
              "      <td>0.10030</td>\n",
              "      <td>0.13280</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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>564</th>\n",
              "      <td>21.56</td>\n",
              "      <td>22.39</td>\n",
              "      <td>142.00</td>\n",
              "      <td>1479.0</td>\n",
              "      <td>0.11100</td>\n",
              "      <td>0.11590</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>565</th>\n",
              "      <td>20.13</td>\n",
              "      <td>28.25</td>\n",
              "      <td>131.20</td>\n",
              "      <td>1261.0</td>\n",
              "      <td>0.09780</td>\n",
              "      <td>0.10340</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>566</th>\n",
              "      <td>16.60</td>\n",
              "      <td>28.08</td>\n",
              "      <td>108.30</td>\n",
              "      <td>858.1</td>\n",
              "      <td>0.08455</td>\n",
              "      <td>0.10230</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>567</th>\n",
              "      <td>20.60</td>\n",
              "      <td>29.33</td>\n",
              "      <td>140.10</td>\n",
              "      <td>1265.0</td>\n",
              "      <td>0.11780</td>\n",
              "      <td>0.27700</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>568</th>\n",
              "      <td>7.76</td>\n",
              "      <td>24.54</td>\n",
              "      <td>47.92</td>\n",
              "      <td>181.0</td>\n",
              "      <td>0.05263</td>\n",
              "      <td>0.04362</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>569 rows × 6 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "     mean radius  mean texture  ...  mean smoothness  mean compactness\n",
              "0          17.99         10.38  ...          0.11840           0.27760\n",
              "1          20.57         17.77  ...          0.08474           0.07864\n",
              "2          19.69         21.25  ...          0.10960           0.15990\n",
              "3          11.42         20.38  ...          0.14250           0.28390\n",
              "4          20.29         14.34  ...          0.10030           0.13280\n",
              "..           ...           ...  ...              ...               ...\n",
              "564        21.56         22.39  ...          0.11100           0.11590\n",
              "565        20.13         28.25  ...          0.09780           0.10340\n",
              "566        16.60         28.08  ...          0.08455           0.10230\n",
              "567        20.60         29.33  ...          0.11780           0.27700\n",
              "568         7.76         24.54  ...          0.05263           0.04362\n",
              "\n",
              "[569 rows x 6 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 94
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "q6PAzubsuOIc"
      },
      "source": [
        "X_train, X_test, y_train, y_test = train_test_split(df, d['target'], test_size=0.33, random_state=42)"
      ],
      "execution_count": 95,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wxZIC9UXsXJ3"
      },
      "source": [
        "# Without power transformation"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 612
        },
        "id": "rQZtNO56tI8X",
        "outputId": "09365034-de90-47ce-ba45-65c94f52dbbe"
      },
      "source": [
        "X_train.hist()\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": 96,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x720 with 6 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cQwmKMuwt_yM",
        "outputId": "cbf754ec-8e14-4971-fbf6-b658c40be066"
      },
      "source": [
        "model = Pipeline([\n",
        "                  ('scaler',StandardScaler()),\n",
        "                  ('model',KNeighborsClassifier())\n",
        "])\n",
        "\n",
        "model.fit(X_train,y_train)\n",
        "\n",
        "roc_auc_score(y_test,model.predict_proba(X_test)[:,1])"
      ],
      "execution_count": 97,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.9764401134821759"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 97
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "yLLEjhgiuvBt"
      },
      "source": [
        "# With power transformation"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 612
        },
        "id": "wZkorwGduzaV",
        "outputId": "8a28aa2b-b340-4092-a697-ca96412a5442"
      },
      "source": [
        "pd.DataFrame(PowerTransformer().fit_transform(X_train),columns=X_train.columns).hist()\n",
        "\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": 98,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x720 with 6 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 612
        },
        "id": "IFFFA9h0zKTL",
        "outputId": "6f3115cb-0b92-45bd-821d-f3f1693457f3"
      },
      "source": [
        "pd.DataFrame(PowerTransformer(method='box-cox').fit_transform(X_train),columns=X_train.columns).hist()\n",
        "\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": 99,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x720 with 6 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jFobdj6luwpC",
        "outputId": "17bd33c0-8a17-4abe-eab6-fc096e157832"
      },
      "source": [
        "model = Pipeline([\n",
        "                  ('power',PowerTransformer()),\n",
        "                  ('scaler',StandardScaler()),\n",
        "                  ('model',KNeighborsClassifier())\n",
        "])\n",
        "\n",
        "model.fit(X_train,y_train)\n",
        "\n",
        "roc_auc_score(y_test,model.predict_proba(X_test)[:,1])"
      ],
      "execution_count": 100,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.9862464536820031"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 100
        }
      ]
    }
  ]
}