Practice_LungCancer.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Practice_LungCancer.ipynb",
      "provenance": [],
      "authorship_tag": "ABX9TyOHfK7OSeoCnnzLnxMY4S5/",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/Giradon/TIL/blob/master/Practice_LungCancer.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "- logistic model 만들어 해석하기\n",
        "- valid model로 predict 하기"
      ],
      "metadata": {
        "id": "WLUaXm_2_3hR"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Sg_35sa6_BR4",
        "outputId": "f3bbda2d-1843-49b6-fe89-89fac1c7cdc3"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/statsmodels/tools/_testing.py:19: FutureWarning: pandas.util.testing is deprecated. Use the functions in the public API at pandas.testing instead.\n",
            "  import pandas.util.testing as tm\n"
          ]
        }
      ],
      "source": [
        "from sklearn.linear_model import LinearRegression\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import statsmodels.api as sm"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "df = pd.read_csv('/Train.csv')\n",
        "test = pd.read_csv('/Valid.csv')\n",
        "print(df.head())\n",
        "print(test.head())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "dAy3FdgT_Ims",
        "outputId": "2c358481-54be-4238-c803-d2f7c8ebb859"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "   Relapse  CEA_Post  Lymphatic  Vascular  pStage  pT  pN  Perineural  Age\n",
            "0        0       0.0          0         0       4   2   2           0   73\n",
            "1        0       1.2          1         0       4   2   2           1   73\n",
            "2        1       1.8          1         0       4   1   2           0   53\n",
            "3        0       0.0          1         0       4   2   2           0   57\n",
            "4        1      52.0          1         1       6   4   3           0   65\n",
            "   Relapse  CEA_Post  Lymphatic  Vascular  pStage  pT  pN  Perineural  Age\n",
            "0        0       1.2          1         0       5   1   3           0   42\n",
            "1        1       1.0          1         0       4   2   2           0   45\n",
            "2        1       9.2          1         0       6   4   3           0   69\n",
            "3        1       0.0          0         0       5   5   1           0   64\n",
            "4        0       2.3          1         1       5   1   3           0   72\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "relapse를 label으로 넣고 유의미한것들로 모델 만들기"
      ],
      "metadata": {
        "id": "fOSGiPTx_dqd"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 상관계수 행렬\n",
        "df_corr = df.corr()\n",
        "\n",
        "# 히트맵 그리기\n",
        "plt.figure(figsize=(10, 10))\n",
        "sns.set(font_scale=0.8)\n",
        "sns.heatmap(df_corr, annot=True, cbar=False);\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 593
        },
        "id": "FbLI6ru6MLlK",
        "outputId": "0e304ef2-07f2-46c2-a66c-b6dc5f1b301e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x720 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 변수 간의 상관관계 분석 - Target 변수와 상관관계가 높은 순서대로 정리\n",
        "corr_order = df_corr.loc[:'Age', 'Relapse'].abs().sort_values(ascending=False)\n",
        "corr_order"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "OoFZML27MdRy",
        "outputId": "f5debd9a-c3a0-485c-ebba-6ca360bff653"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Relapse       1.000000\n",
              "Vascular      0.208355\n",
              "Lymphatic     0.206385\n",
              "pN            0.204281\n",
              "pStage        0.180064\n",
              "CEA_Post      0.163411\n",
              "Perineural    0.130624\n",
              "pT            0.056499\n",
              "Age           0.001398\n",
              "Name: Relapse, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 41
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import seaborn as sns\n",
        "sns.pairplot(df)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 942
        },
        "id": "qh6EI0r__bpZ",
        "outputId": "37845e4c-a531-45a9-b7cf-76821875b875"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.PairGrid at 0x7f0102db8850>"
            ]
          },
          "metadata": {},
          "execution_count": 5
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1620x1620 with 90 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "Label = df['Relapse']\n",
        "InputFeature = df[['CEA_Post', 'Lymphatic', 'Vascular', 'pStage', 'pT', 'pN', 'Perineural', 'Age']]"
      ],
      "metadata": {
        "id": "HmlJTJnqBSPA"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "plt.plot(InputFeature['CEA_Post'], Label, 'o')\n",
        "plt.show()\n",
        "\n",
        "plt.plot(InputFeature['Lymphatic'], Label, 'o')\n",
        "plt.show()\n",
        "\n",
        "plt.plot(InputFeature['Vascular'], Label, 'o')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 761
        },
        "id": "L1yX1UDbJ_hB",
        "outputId": "017dc056-aa7f-45e8-af05-156cefa29326"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "InputFeature = sm.add_constant(InputFeature)\n",
        "model = sm.Logit(Label, InputFeature)\n",
        "model = model.fit()\n",
        "print(model.params)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "uL_K9Ry7DBjv",
        "outputId": "5a05ab73-d039-4b19-d791-2cf512630e39"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Optimization terminated successfully.\n",
            "         Current function value: 0.614428\n",
            "         Iterations 8\n",
            "const        -1.969500\n",
            "CEA_Post      0.018205\n",
            "Lymphatic     0.639076\n",
            "Vascular      0.582773\n",
            "pStage       -0.159252\n",
            "pT            0.240697\n",
            "pN            0.511047\n",
            "Perineural    0.304236\n",
            "Age          -0.003822\n",
            "dtype: float64\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/statsmodels/tsa/tsatools.py:117: FutureWarning: In a future version of pandas all arguments of concat except for the argument 'objs' will be keyword-only\n",
            "  x = pd.concat(x[::order], 1)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print( model.summary() )"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "u0X8FxCnDGIi",
        "outputId": "bb7bf4fe-906e-4601-c5d1-d6e85eb8adf8"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "                           Logit Regression Results                           \n",
            "==============================================================================\n",
            "Dep. Variable:                Relapse   No. Observations:                  392\n",
            "Model:                          Logit   Df Residuals:                      383\n",
            "Method:                           MLE   Df Model:                            8\n",
            "Date:                Fri, 15 Apr 2022   Pseudo R-squ.:                 0.09721\n",
            "Time:                        07:13:14   Log-Likelihood:                -240.86\n",
            "converged:                       True   LL-Null:                       -266.79\n",
            "Covariance Type:            nonrobust   LLR p-value:                 1.785e-08\n",
            "==============================================================================\n",
            "                 coef    std err          z      P>|z|      [0.025      0.975]\n",
            "------------------------------------------------------------------------------\n",
            "const         -1.9695      0.828     -2.378      0.017      -3.593      -0.346\n",
            "CEA_Post       0.0182      0.009      2.127      0.033       0.001       0.035\n",
            "Lymphatic      0.6391      0.261      2.445      0.014       0.127       1.151\n",
            "Vascular       0.5828      0.232      2.510      0.012       0.128       1.038\n",
            "pStage        -0.1593      0.263     -0.604      0.546      -0.676       0.357\n",
            "pT             0.2407      0.157      1.538      0.124      -0.066       0.548\n",
            "pN             0.5110      0.357      1.430      0.153      -0.189       1.211\n",
            "Perineural     0.3042      0.358      0.849      0.396      -0.398       1.007\n",
            "Age           -0.0038      0.012     -0.324      0.746      -0.027       0.019\n",
            "==============================================================================\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Logistic regression 모델 해석하기\n",
        "Coefficient: ln ( odds ) = 0.0182 * CEA_Post + 0.6391 * Lymphatic + 0.5828 * Vascular + const\n",
        "\n",
        "odds를 알기 위해서는 exponential을 해주어야한다. (log 없애기)"
      ],
      "metadata": {
        "id": "86ZES-ZKGspG"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "valid = test[['CEA_Post', 'Lymphatic', 'Vascular', 'pStage', 'Perineural']]"
      ],
      "metadata": {
        "id": "fQ34-kULQwtJ"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "np.exp(model.params).round(4)"
      ],
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        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "H-wU1qTrDJbO",
        "outputId": "3f79866a-cabc-4bcf-ba16-e7f45e1da20f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "const         0.1395\n",
              "CEA_Post      1.0184\n",
              "Lymphatic     1.8947\n",
              "Vascular      1.7910\n",
              "pStage        0.8528\n",
              "pT            1.2721\n",
              "pN            1.6670\n",
              "Perineural    1.3556\n",
              "Age           0.9962\n",
              "dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df[['CEA_Post','Lymphatic', 'Vascular']]"
      ],
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          "height": 424
        },
        "id": "Xti71DT2GZ1I",
        "outputId": "98d1070e-6520-4fb7-f44c-752421f27714"
      },
      "execution_count": null,
      "outputs": [
        {
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            "text/plain": [
              "     CEA_Post  Lymphatic  Vascular\n",
              "0         0.0          0         0\n",
              "1         1.2          1         0\n",
              "2         1.8          1         0\n",
              "3         0.0          1         0\n",
              "4        52.0          1         1\n",
              "..        ...        ...       ...\n",
              "387       1.7          0         0\n",
              "388       4.1          0         0\n",
              "389       2.2          1         0\n",
              "390       5.2          0         0\n",
              "391       2.8          1         0\n",
              "\n",
              "[392 rows x 3 columns]"
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        "plt.show()"
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        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.plot(model.predict(test), test['Vascular'], 'o')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 267
        },
        "id": "fey0jkx9JNrO",
        "outputId": "b82aba7f-1111-46ad-9534-fe4f5bb337cf"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "Lymphatic"
      ],
      "metadata": {
        "id": "1zc-OR9RKwMK"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        ""
      ],
      "metadata": {
        "id": "hHCBpjsCEa5A"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}