ensemble_v1_2.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "<text style=\"color:green;font-size: 250%\">Попытка ID\t5769352</text><br>\n",
        "<text style=\"color:green;font-size: 120%\">Решение параллельным ансамблем из Catboost и LightGBM</text>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "SNgzYcGpTLwM"
      },
      "source": [
        "## Описание полей"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UebqlsM9WbZQ"
      },
      "source": [
        "В датасете собраны данные о пользователях телекоммуникационной компании:\n",
        "\n",
        "*   State - штат\n",
        "*   Account length - как долго этот клиент с компанией (количество дней)\n",
        "*   Area code - код географической зоны\n",
        "*   International plan - подключен ли спец тариф для международных звонков\n",
        "*   Voice mail plan - подключен сервис голосовых сообщений\n",
        "*   Number vmail messages - количество голосовых сообщений\n",
        "*   Total day minutes - продолжительность разговоров в дневное время (минуты) \n",
        "*   Total day calls - количество звонков в дневное время\n",
        "*   Total day charge - расходы на звонки в дневное время\n",
        "*   Total eve minutes - продолжительность разговоров в вечернее время\n",
        "*   Total eve calls - количество звонков в вечернее время\n",
        "*   Total eve charge - расходы на звонки в вечернее время\n",
        "*   Total night minutes - продолжительность разговоров в ночное время\n",
        "*   Total night calls - количество звонков в дневное время\n",
        "*   Total night charge - расходы на звонки в вечернее время\n",
        "*   Total intl minutes - продолжительность международных звонков\n",
        "*   Total intl calls - количество международных звонков\n",
        "*   Total intl charge - расходы на межденародные звонки \n",
        "*   Customer service calls - количество обращений в службу поддержки\n",
        "*   Churn - текущий статус клиента (ушел/остался)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "# Решение"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Перечень установленных пакетов"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {},
      "outputs": [],
      "source": [
        "!pip freeze > requirements.txt"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Package                       Version\n",
            "----------------------------- ---------\n",
            "absl-py                       1.0.0\n",
            "argon2-cffi                   21.1.0\n",
            "astunparse                    1.6.3\n",
            "attrs                         21.2.0\n",
            "backcall                      0.2.0\n",
            "backports.functools-lru-cache 1.6.4\n",
            "bleach                        4.1.0\n",
            "cachetools                    4.2.4\n",
            "catboost                      1.0.3\n",
            "certifi                       2021.10.8\n",
            "cffi                          1.15.0\n",
            "charset-normalizer            2.0.7\n",
            "colorama                      0.4.4\n",
            "colorlover                    0.3.0\n",
            "cufflinks                     0.17.3\n",
            "cycler                        0.11.0\n",
            "debugpy                       1.5.1\n",
            "decorator                     5.1.0\n",
            "defusedxml                    0.7.1\n",
            "entrypoints                   0.3\n",
            "flatbuffers                   2.0\n",
            "gast                          0.4.0\n",
            "google-auth                   2.3.3\n",
            "google-auth-oauthlib          0.4.6\n",
            "google-pasta                  0.2.0\n",
            "graphviz                      0.18\n",
            "grpcio                        1.41.1\n",
            "h5py                          3.5.0\n",
            "idna                          3.3\n",
            "importlib-resources           5.4.0\n",
            "ipykernel                     6.5.0\n",
            "ipython                       7.29.0\n",
            "ipython-genutils              0.2.0\n",
            "ipywidgets                    7.6.5\n",
            "jedi                          0.18.0\n",
            "Jinja2                        3.0.3\n",
            "joblib                        1.1.0\n",
            "jsonschema                    4.2.1\n",
            "jupyter-client                7.0.6\n",
            "jupyter-core                  4.9.1\n",
            "jupyterlab-pygments           0.1.2\n",
            "jupyterlab-widgets            1.0.2\n",
            "keras                         2.7.0\n",
            "Keras-Preprocessing           1.1.2\n",
            "kiwisolver                    1.3.2\n",
            "libclang                      12.0.0\n",
            "lightgbm                      3.3.1\n",
            "Markdown                      3.3.4\n",
            "MarkupSafe                    2.0.1\n",
            "matplotlib                    3.4.3\n",
            "matplotlib-inline             0.1.3\n",
            "mistune                       0.8.4\n",
            "nbclient                      0.5.8\n",
            "nbconvert                     6.3.0\n",
            "nbformat                      5.1.3\n",
            "nest-asyncio                  1.5.1\n",
            "notebook                      6.4.5\n",
            "numpy                         1.21.4\n",
            "oauthlib                      3.1.1\n",
            "opt-einsum                    3.3.0\n",
            "packaging                     21.2\n",
            "pandas                        1.3.4\n",
            "pandocfilters                 1.5.0\n",
            "parso                         0.8.2\n",
            "pickleshare                   0.7.5\n",
            "Pillow                        8.4.0\n",
            "pip                           21.3.1\n",
            "plotly                        5.3.1\n",
            "prometheus-client             0.12.0\n",
            "prompt-toolkit                3.0.22\n",
            "protobuf                      3.19.1\n",
            "pyasn1                        0.4.8\n",
            "pyasn1-modules                0.2.8\n",
            "pycparser                     2.21\n",
            "Pygments                      2.10.0\n",
            "pyparsing                     2.4.7\n",
            "pyrsistent                    0.18.0\n",
            "python-dateutil               2.8.2\n",
            "pytz                          2021.3\n",
            "pywin32                       302\n",
            "pywinpty                      1.1.5\n",
            "pyzmq                         22.3.0\n",
            "requests                      2.26.0\n",
            "requests-oauthlib             1.3.0\n",
            "rsa                           4.7.2\n",
            "scikit-learn                  1.0.1\n",
            "scipy                         1.7.2\n",
            "seaborn                       0.11.2\n",
            "Send2Trash                    1.8.0\n",
            "setuptools                    58.5.3\n",
            "six                           1.16.0\n",
            "tenacity                      8.0.1\n",
            "tensorboard                   2.7.0\n",
            "tensorboard-data-server       0.6.1\n",
            "tensorboard-plugin-wit        1.8.0\n",
            "tensorflow                    2.7.0\n",
            "tensorflow-estimator          2.7.0\n",
            "tensorflow-io-gcs-filesystem  0.22.0\n",
            "termcolor                     1.1.0\n",
            "terminado                     0.12.1\n",
            "testpath                      0.5.0\n",
            "threadpoolctl                 3.0.0\n",
            "tornado                       6.1\n",
            "tqdm                          4.62.3\n",
            "traitlets                     5.1.1\n",
            "typing-extensions             3.10.0.2\n",
            "urllib3                       1.26.7\n",
            "wcwidth                       0.2.5\n",
            "webencodings                  0.5.1\n",
            "Werkzeug                      2.0.2\n",
            "wheel                         0.37.0\n",
            "widgetsnbextension            3.5.2\n",
            "wrapt                         1.13.3\n",
            "xgboost                       1.5.0\n",
            "zipp                          3.6.0\n"
          ]
        }
      ],
      "source": [
        "!pip list"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {},
      "outputs": [],
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "import seaborn as sns\n",
        "from sklearn.compose import ColumnTransformer\n",
        "from sklearn.ensemble import RandomForestClassifier\n",
        "from sklearn.feature_selection import SelectKBest, f_classif\n",
        "from sklearn.linear_model import LogisticRegression\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.pipeline import Pipeline\n",
        "from sklearn.preprocessing import OneHotEncoder, StandardScaler\n",
        "from sklearn.svm import SVC\n",
        "\n",
        "import lightgbm as lgb\n",
        "from catboost import CatBoostClassifier, Pool\n",
        "from tensorflow import keras\n",
        "from tensorflow.keras import layers\n",
        "from xgboost import XGBClassifier"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {},
      "outputs": [],
      "source": [
        "import warnings\n",
        "warnings.filterwarnings(\"ignore\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {},
      "outputs": [],
      "source": [
        "train = pd.read_csv('train.csv')\n",
        "test = pd.read_csv('test.csv')\n",
        "\n",
        "train['International plan'] = train['International plan'].replace({\"Yes\":1,\"No\":0}).astype('int64')\n",
        "train['Voice mail plan'] = train['Voice mail plan'].replace({\"Yes\":1,\"No\":0}).astype('int64')\n",
        "\n",
        "test['International plan'] = test['International plan'].replace({\"Yes\":1,\"No\":0}).astype('int64')\n",
        "test['Voice mail plan'] = test['Voice mail plan'].replace({\"Yes\":1,\"No\":0}).astype('int64')\n",
        "\n",
        "columns_to_del = ['State', 'Area code', 'Total day charge', 'Total eve charge', 'Total night charge', 'Total intl charge', 'Voice mail plan']\n",
        "\n",
        "train = train.drop(columns_to_del, axis = 1)\n",
        "test = test.drop(columns_to_del, axis = 1)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {},
      "outputs": [
        {
          "data": {
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",
            "text/plain": [
              "<Figure size 1008x864 with 2 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "colormap = plt.cm.RdBu\n",
        "plt.figure(figsize=(14,12))\n",
        "plt.title('Correlation of Features', y=1, size=15)\n",
        "sns.heatmap(train.corr(),linewidths=0.1,vmax=1.0, \n",
        "            square=True, cmap=colormap, linecolor='white', annot=True, fmt='.2g')\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "# <text style=\"color:red; font-size:120%\">Ансамбль классификации</text>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Сформируем параллельный ансамбль из моделей LightGBM и Catbost, с заранее выбранными гиперпараметрами.\n",
        "Итоговое предсказание рассчитаем на основании равноправного голосования."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {},
      "outputs": [],
      "source": [
        "def func_prep():\n",
        "    categorical_features = ['International plan']\n",
        "    numeric_features = X_train.columns.drop(categorical_features)\n",
        "\n",
        "    numeric_transformer = StandardScaler()\n",
        "    categorical_transformer = OneHotEncoder(handle_unknown=\"ignore\")\n",
        "\n",
        "    preprocessor = ColumnTransformer(\n",
        "        transformers=[\n",
        "            (\"num\", numeric_transformer, numeric_features),\n",
        "            (\"cat\", categorical_transformer, categorical_features),\n",
        "        ]\n",
        "    )\n",
        "    return preprocessor\n",
        "\n",
        "def pipe_with_transform(clf, bool_prep=True, bool_select=True, k_feat=13):\n",
        "    arr = []\n",
        "    if bool_prep:\n",
        "        preprocessor = func_prep()\n",
        "        arr.append((\"scl\", preprocessor))\n",
        "    if bool_select:\n",
        "        selector = SelectKBest(f_classif, k=k_feat)\n",
        "        arr.append(('feature_selection', selector))\n",
        "    arr.append((\"clf\", clf))\n",
        "    return Pipeline(arr)\n",
        "\n",
        "\n",
        "# Функция необходима для выбора класса при \"мягком\" голосования\n",
        "def vote_class (x):\n",
        "    a = np.argmax(x.values)\n",
        "    return a"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Поищим лучшие веса для вероятностей"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "# Подготовка предсказания"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {},
      "outputs": [],
      "source": [
        "X_train = train.drop(columns='Churn')\n",
        "y_train = train['Churn']\n",
        "X_test = test"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "### Модель LightGBM"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        }
      ],
      "source": [
        "pipe_lgbm = pipe_with_transform(\n",
        "    lgb.LGBMRegressor(\n",
        "        max_depth=5,\n",
        "        min_child_samples=2\n",
        "    ), \n",
        "    bool_select=False\n",
        "    )\n",
        "pipe_lgbm.fit(X_train, y_train)\n",
        "print()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "### Модель Catboost"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 15,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        }
      ],
      "source": [
        "preprocessor_cb = func_prep()\n",
        "x_train_transform = preprocessor_cb.fit_transform(X_train)\n",
        "train_dataset = Pool(data=x_train_transform, label=y_train)\n",
        "\n",
        "model_catboost = CatBoostClassifier(\n",
        "        iterations=100,\n",
        "        learning_rate=0.4,\n",
        "        depth=4,\n",
        "        l2_leaf_reg=4,\n",
        "        loss_function=\"Logloss\",\n",
        "        bootstrap_type=\"MVS\",\n",
        "        custom_metric=\"F1\"\n",
        "        )\n",
        "\n",
        "model_catboost.fit(train_dataset, verbose=0)\n",
        "print()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {},
      "outputs": [],
      "source": [
        "target_test_lgb_proba = 1 - pd.DataFrame(pipe_lgbm.predict(X_test))\n",
        "target_test_lgb_proba[1] = 1 - target_test_lgb_proba[0]\n",
        "target_test_cb_proba = pd.DataFrame(\n",
        "    model_catboost.predict_proba(\n",
        "        Pool(data=preprocessor_cb.transform(X_test))\n",
        "        ))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {},
      "outputs": [],
      "source": [
        "target_test_proba = target_test_lgb_proba\n",
        "for i in range(0, 2):\n",
        "    target_test_proba[i] += target_test_cb_proba[i]\n",
        "target_test_proba[\"Churn\"] = target_test_proba.apply(vote_class, axis=1)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "<text style=\"color:green;font-size: 250%\">Итоговое предсказание ID\t5769352</text>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 14,
      "metadata": {},
      "outputs": [],
      "source": [
        "target_test_proba[\"Churn\"].astype('bool').to_csv('submit_lgb_cb.csv')"
      ]
    }
  ],
  "metadata": {
    "colab": {
      "name": "Baseline.ipynb",
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.8.12"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}