Naive_Bayes__lung_cancer_predict.ipynb

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      "execution_count": 113,
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        "id": "2uw7xhTU21Ry"
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      "source": [
        "# source DATA https://www.kaggle.com/datasets/imkrkannan/lung-cancer-dataset-by-staceyinrobert\n",
        "# Lê Tuấn Kiệt"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# import thư viện pandas và numpy\n",
        "\n",
        "import numpy as np\n",
        "import pandas as pd"
      ],
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        "id": "MxVdd8cA4DqS"
      },
      "execution_count": 114,
      "outputs": []
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      "source": [
        "# đọc data\n",
        "data = pd.read_csv('/content/survey_lung_cancer.csv')\n",
        "\n",
        "# show 5 dòng đầu \n",
        "data.head(5)"
      ],
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              "   GENDER  AGE  SMOKING  YELLOW_FINGERS  ANXIETY  PEER_PRESSURE  \\\n",
              "0    MALE   69        0               1        1              0   \n",
              "1    MALE   74        1               0        0              0   \n",
              "2  FEMALE   59        0               0        0              1   \n",
              "3    MALE   63        1               1        1              0   \n",
              "4  FEMALE   63        0               1        0              0   \n",
              "\n",
              "   CHRONIC DISEASE  FATIGUE   ALLERGY   WHEEZING  ALCOHOL CONSUMING  COUGHING  \\\n",
              "0                0         1         0         1                  1         1   \n",
              "1                1         1         1         0                  0         0   \n",
              "2                0         1         0         1                  0         1   \n",
              "3                0         0         0         0                  1         0   \n",
              "4                0         0         0         1                  0         1   \n",
              "\n",
              "   SHORTNESS OF BREATH  SWALLOWING DIFFICULTY  CHEST PAIN LUNG_CANCER  \n",
              "0                    1                      1           1         YES  \n",
              "1                    1                      1           1         YES  \n",
              "2                    1                      0           1          NO  \n",
              "3                    0                      1           1          NO  \n",
              "4                    1                      0           0          NO  "
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              "      <th>GENDER</th>\n",
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    {
      "cell_type": "code",
      "source": [
        "# info\n",
        "data.info\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7OXo2Wb_4xuC",
        "outputId": "36a59608-3b65-47ac-f3d3-372a2ecaa85b"
      },
      "execution_count": 116,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<bound method DataFrame.info of      GENDER  AGE  SMOKING  YELLOW_FINGERS  ANXIETY  PEER_PRESSURE  \\\n",
              "0      MALE   69        0               1        1              0   \n",
              "1      MALE   74        1               0        0              0   \n",
              "2    FEMALE   59        0               0        0              1   \n",
              "3      MALE   63        1               1        1              0   \n",
              "4    FEMALE   63        0               1        0              0   \n",
              "..      ...  ...      ...             ...      ...            ...   \n",
              "304  FEMALE   56        0               0        0              1   \n",
              "305    MALE   70        1               0        0              0   \n",
              "306    MALE   58        1               0        0              0   \n",
              "307    MALE   67        1               0        1              0   \n",
              "308    MALE   62        0               0        0              1   \n",
              "\n",
              "     CHRONIC DISEASE  FATIGUE   ALLERGY   WHEEZING  ALCOHOL CONSUMING  \\\n",
              "0                  0         1         0         1                  1   \n",
              "1                  1         1         1         0                  0   \n",
              "2                  0         1         0         1                  0   \n",
              "3                  0         0         0         0                  1   \n",
              "4                  0         0         0         1                  0   \n",
              "..               ...       ...       ...       ...                ...   \n",
              "304                1         1         0         0                  1   \n",
              "305                0         1         1         1                  1   \n",
              "306                0         0         1         1                  1   \n",
              "307                0         1         1         0                  1   \n",
              "308                0         1         1         1                  1   \n",
              "\n",
              "     COUGHING  SHORTNESS OF BREATH  SWALLOWING DIFFICULTY  CHEST PAIN  \\\n",
              "0           1                    1                      1           1   \n",
              "1           0                    1                      1           1   \n",
              "2           1                    1                      0           1   \n",
              "3           0                    0                      1           1   \n",
              "4           1                    1                      0           0   \n",
              "..        ...                  ...                    ...         ...   \n",
              "304         1                    1                      1           0   \n",
              "305         1                    1                      0           1   \n",
              "306         1                    0                      0           1   \n",
              "307         1                    1                      0           1   \n",
              "308         0                    0                      1           0   \n",
              "\n",
              "    LUNG_CANCER  \n",
              "0           YES  \n",
              "1           YES  \n",
              "2            NO  \n",
              "3            NO  \n",
              "4            NO  \n",
              "..          ...  \n",
              "304         YES  \n",
              "305         YES  \n",
              "306         YES  \n",
              "307         YES  \n",
              "308         YES  \n",
              "\n",
              "[309 rows x 16 columns]>"
            ]
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          "metadata": {},
          "execution_count": 116
        }
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    {
      "cell_type": "code",
      "source": [
        "# ktra có dữ liệu khuyết không\n",
        "data.isnull().values.any()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "zTUIJu_948ak",
        "outputId": "beabf9ce-f70d-4e98-e352-ee0c879afeaf"
      },
      "execution_count": 117,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "False"
            ]
          },
          "metadata": {},
          "execution_count": 117
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# đếm giá trị của cột mục tiêu (LUNG_CANCER)\n",
        "data[\"LUNG_CANCER\"].value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "82BncxV45FZq",
        "outputId": "cc826a04-3375-4e21-9062-ef94f9699497"
      },
      "execution_count": 118,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "YES    270\n",
              "NO      39\n",
              "Name: LUNG_CANCER, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 118
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Trực quan hoá cột (LUNG_CANCER)\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "plt.figure(figsize = (4,4))\n",
        "plt.title(\"Total data yes and no\",fontsize=13)\n",
        "plt.xlabel(\"lung_cancer\", fontsize=13)\n",
        "plt.ylabel(\"case\",fontsize=13)\n",
        "data[\"LUNG_CANCER\"].value_counts().plot(kind= 'bar',fontsize=13)\n",
        "plt.show()"
      ],
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          "height": 313
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      },
      "execution_count": 119,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 288x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# xử lý data cột GENDER và cột LUNG_CANCER về kiểu số\n",
        "\n",
        "data['GENDER'] = data['GENDER'].apply(lambda x: 1 if x=='MALE' else 0)\n",
        "data['LUNG_CANCER'] = data['LUNG_CANCER'].apply(lambda x: 1 if x=='YES' else 0)\n",
        "data.head(5)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 267
        },
        "id": "0_W3N9Vz6hnX",
        "outputId": "42e60e41-1808-4236-b45c-592433b910ad"
      },
      "execution_count": 120,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   GENDER  AGE  SMOKING  YELLOW_FINGERS  ANXIETY  PEER_PRESSURE  \\\n",
              "0       1   69        0               1        1              0   \n",
              "1       1   74        1               0        0              0   \n",
              "2       0   59        0               0        0              1   \n",
              "3       1   63        1               1        1              0   \n",
              "4       0   63        0               1        0              0   \n",
              "\n",
              "   CHRONIC DISEASE  FATIGUE   ALLERGY   WHEEZING  ALCOHOL CONSUMING  COUGHING  \\\n",
              "0                0         1         0         1                  1         1   \n",
              "1                1         1         1         0                  0         0   \n",
              "2                0         1         0         1                  0         1   \n",
              "3                0         0         0         0                  1         0   \n",
              "4                0         0         0         1                  0         1   \n",
              "\n",
              "   SHORTNESS OF BREATH  SWALLOWING DIFFICULTY  CHEST PAIN  LUNG_CANCER  \n",
              "0                    1                      1           1            1  \n",
              "1                    1                      1           1            1  \n",
              "2                    1                      0           1            0  \n",
              "3                    0                      1           1            0  \n",
              "4                    1                      0           0            0  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-5b066469-962c-4886-8bcf-9f5412da42ae\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>GENDER</th>\n",
              "      <th>AGE</th>\n",
              "      <th>SMOKING</th>\n",
              "      <th>YELLOW_FINGERS</th>\n",
              "      <th>ANXIETY</th>\n",
              "      <th>PEER_PRESSURE</th>\n",
              "      <th>CHRONIC DISEASE</th>\n",
              "      <th>FATIGUE</th>\n",
              "      <th>ALLERGY</th>\n",
              "      <th>WHEEZING</th>\n",
              "      <th>ALCOHOL CONSUMING</th>\n",
              "      <th>COUGHING</th>\n",
              "      <th>SHORTNESS OF BREATH</th>\n",
              "      <th>SWALLOWING DIFFICULTY</th>\n",
              "      <th>CHEST PAIN</th>\n",
              "      <th>LUNG_CANCER</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>69</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>74</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0</td>\n",
              "      <td>59</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1</td>\n",
              "      <td>63</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0</td>\n",
              "      <td>63</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-5b066469-962c-4886-8bcf-9f5412da42ae')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-5b066469-962c-4886-8bcf-9f5412da42ae button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-5b066469-962c-4886-8bcf-9f5412da42ae');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 120
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# import sklearn\n",
        "\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.metrics import accuracy_score\n",
        "from sklearn.metrics import classification_report\n",
        "from sklearn import metrics"
      ],
      "metadata": {
        "id": "SIcxGHBK7fBG"
      },
      "execution_count": 121,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# select 15 cột đầu for x ; cột LUNG_CANCER for y\n",
        "# sử dụng iloc vì nó nhanh hơn,  data.iloc[<row selection>,<column selection>]\n",
        "\n",
        "x = data.iloc[ :,[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14]].values\n",
        "y = data[\"LUNG_CANCER\"].values\n",
        "x"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "V-hXIwtn7v-M",
        "outputId": "7370076b-58f4-486f-9ba6-662f1b2c0d1a"
      },
      "execution_count": 122,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[ 1, 69,  0, ...,  1,  1,  1],\n",
              "       [ 1, 74,  1, ...,  1,  1,  1],\n",
              "       [ 0, 59,  0, ...,  1,  0,  1],\n",
              "       ...,\n",
              "       [ 1, 58,  1, ...,  0,  0,  1],\n",
              "       [ 1, 67,  1, ...,  1,  0,  1],\n",
              "       [ 1, 62,  0, ...,  0,  1,  0]])"
            ]
          },
          "metadata": {},
          "execution_count": 122
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# chia tập train:test theo tỉ lệ 75:25 để đánh giá hiệu xuất; thiết lập random_state seed = (19 có độ chính xác khá cao )\n",
        "\n",
        "x_train, x_test, y_train, y_test = train_test_split(x, y ,test_size=0.25 , random_state=19)\n",
        "print('x_train: ',x_train.shape)\n",
        "print('x_test: ', x_test.shape)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "AbhkM6Ea-G5h",
        "outputId": "b4753086-bc0b-44d0-ffe2-74516ed8b674"
      },
      "execution_count": 123,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "x_train:  (231, 15)\n",
            "x_test:  (78, 15)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# naive bayes trên tập train\n",
        "\n",
        "from sklearn.naive_bayes import GaussianNB\n",
        "\n",
        "model = GaussianNB()\n",
        "model.fit(x_train, y_train)\n",
        "model.predict(x_train)\n",
        "print(\"accuracy = \" ,accuracy_score(y_test, model.predict(x_test)))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "WF-IEhCP_4sS",
        "outputId": "d5303785-9dd0-4225-b11c-de58ac0ebe5c"
      },
      "execution_count": 124,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "accuracy =  0.9230769230769231\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "model_predict = model.predict(x_test)\n",
        "\n",
        "print('accuracy: {:.2f}'.format(metrics.accuracy_score(y_test, model_predict)))\n",
        "accuracy_score = (metrics.accuracy_score(y_test, model_predict))\n",
        "\n",
        "# True positive (TP) ; False positive (FP)\n",
        "# False negative (FN); True negative (TN)\n",
        "print(metrics.confusion_matrix(y_test, model_predict, labels=[1,0]))\n",
        "\n",
        "# Báo cáo\n",
        "print('\\nClassification Report:')\n",
        "print(metrics.classification_report(y_test, model_predict, labels=[1,0]))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "yXVuFG2CAmi_",
        "outputId": "a0152f63-78b4-4328-e1fe-33b917a7b55e"
      },
      "execution_count": 134,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "accuracy: 0.92\n",
            "[[67  2]\n",
            " [ 4  5]]\n",
            "\n",
            "Classification Report:\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "           1       0.94      0.97      0.96        69\n",
            "           0       0.71      0.56      0.63         9\n",
            "\n",
            "    accuracy                           0.92        78\n",
            "   macro avg       0.83      0.76      0.79        78\n",
            "weighted avg       0.92      0.92      0.92        78\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        " Precision = (TP/(TP+FP) \n",
        "\n",
        " Recall    = (TP/(TP+FN) \n",
        "\n",
        " F1 Score  = (2/((Precision^-1)+(Recall^-1))\n"
      ],
      "metadata": {
        "id": "PBasIKDzFY_Z"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "GENDER=1\n",
        "AGE=20\n",
        "SMOKING =0\n",
        "YELLOW_FINGERS = 0\n",
        "ANXIETY = 0\n",
        "PEER_PRESSURE = 1\n",
        "CHRONIC_DISEASE = 0\n",
        "FATIGUE =1\n",
        "ALLERGY= 0\n",
        "WHEEZING = 1\n",
        "ALCOHOL_CONSUMING = 0\n",
        "COUGHING = 1\n",
        "SHORTNESS_OF_BREATH = 1\n",
        "SWALLOWING_DIFFICULTY = 0\n",
        "CHEST_PAIN =1"
      ],
      "metadata": {
        "id": "3Dr5SVrEFtDA"
      },
      "execution_count": 126,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "model_predict = [[GENDER,AGE,SMOKING,YELLOW_FINGERS,ANXIETY,PEER_PRESSURE ,CHRONIC_DISEASE,FATIGUE,ALLERGY,WHEEZING,ALCOHOL_CONSUMING,COUGHING,SHORTNESS_OF_BREATH,SWALLOWING_DIFFICULTY,CHEST_PAIN]]\n",
        "model_pred =model.predict(model_predict)\n",
        "\n",
        "if model_pred == 1:\n",
        "    result = \"Có dấu hiệu bị ung thư phổi\"\n",
        "elif model_pred == 0 :\n",
        "    result = \"Không có dấu hiệu bị ung thư phổi\"\n",
        "else :\n",
        "    result = \"error \"\n",
        "\n",
        "print(\"Dựa trên thông tin được đưa vào\\n với độ chính xác {:.2f} ta có dự đoán:\\n >> {}\".format((accuracy_score),result))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "a0TwUVP9MnYO",
        "outputId": "125ba418-1dfd-436f-96cd-7782e0ab9972"
      },
      "execution_count": 133,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Dựa trên thông tin được đưa vào\n",
            " với độ chính xác 0.92 ta có dự đoán:\n",
            " >> Không có dấu hiệu bị ung thư phổi\n"
          ]
        }
      ]
    }
  ]
}