colab/Вариант 2/notebook.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "id": "f2485344",
      "metadata": {},
      "source": [
        "# Прогнозирование энергопотребления"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 81,
      "id": "c15bd427",
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m25.3\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m26.0.1\u001b[0m\n",
            "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\n",
            "Note: you may need to restart the kernel to use updated packages.\n"
          ]
        }
      ],
      "source": [
        "%pip -q install pandas numpy matplotlib seaborn scikit-learn"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 82,
      "id": "ad72f151",
      "metadata": {},
      "outputs": [],
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.compose import ColumnTransformer\n",
        "from sklearn.preprocessing import OneHotEncoder\n",
        "from sklearn.pipeline import Pipeline\n",
        "from sklearn.impute import SimpleImputer\n",
        "from sklearn.metrics import mean_absolute_error, mean_squared_error, r2_score\n",
        "from sklearn.linear_model import LinearRegression\n",
        "from sklearn.ensemble import RandomForestRegressor, GradientBoostingRegressor\n",
        "\n",
        "pd.set_option(\"display.max_columns\", 50)\n",
        "sns.set_style(\"whitegrid\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 83,
      "id": "79315a77",
      "metadata": {},
      "outputs": [
        {
          "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>Building Type</th>\n",
              "      <th>Square Footage</th>\n",
              "      <th>Number of Occupants</th>\n",
              "      <th>Appliances Used</th>\n",
              "      <th>Average Temperature</th>\n",
              "      <th>Day of Week</th>\n",
              "      <th>Energy Consumption</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Residential</td>\n",
              "      <td>7063</td>\n",
              "      <td>76</td>\n",
              "      <td>10</td>\n",
              "      <td>29.84</td>\n",
              "      <td>Weekday</td>\n",
              "      <td>2713.95</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Commercial</td>\n",
              "      <td>44372</td>\n",
              "      <td>66</td>\n",
              "      <td>45</td>\n",
              "      <td>16.72</td>\n",
              "      <td>Weekday</td>\n",
              "      <td>5744.99</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Industrial</td>\n",
              "      <td>19255</td>\n",
              "      <td>37</td>\n",
              "      <td>17</td>\n",
              "      <td>14.30</td>\n",
              "      <td>Weekend</td>\n",
              "      <td>4101.24</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Residential</td>\n",
              "      <td>13265</td>\n",
              "      <td>14</td>\n",
              "      <td>41</td>\n",
              "      <td>32.82</td>\n",
              "      <td>Weekday</td>\n",
              "      <td>3009.14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Commercial</td>\n",
              "      <td>13375</td>\n",
              "      <td>26</td>\n",
              "      <td>18</td>\n",
              "      <td>11.92</td>\n",
              "      <td>Weekday</td>\n",
              "      <td>3279.17</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "  Building Type  Square Footage  Number of Occupants  Appliances Used  \\\n",
              "0   Residential            7063                   76               10   \n",
              "1    Commercial           44372                   66               45   \n",
              "2    Industrial           19255                   37               17   \n",
              "3   Residential           13265                   14               41   \n",
              "4    Commercial           13375                   26               18   \n",
              "\n",
              "   Average Temperature Day of Week  Energy Consumption  \n",
              "0                29.84     Weekday             2713.95  \n",
              "1                16.72     Weekday             5744.99  \n",
              "2                14.30     Weekend             4101.24  \n",
              "3                32.82     Weekday             3009.14  \n",
              "4                11.92     Weekday             3279.17  "
            ]
          },
          "execution_count": 83,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Загрузка обучающей выборки\n",
        "df = pd.read_csv(\"train_energy_data.csv\")\n",
        "df.head()"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "667f4766",
      "metadata": {},
      "source": [
        "## Очистка и предобработка\n",
        "\n",
        "- Удаляем дубликаты.\n",
        "- Удаляем пропуски (если есть).\n",
        "- Проверяем типы и качество данных."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 84,
      "id": "e3e30a9f",
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "<class 'pandas.DataFrame'>\n",
            "RangeIndex: 1000 entries, 0 to 999\n",
            "Data columns (total 7 columns):\n",
            " #   Column               Non-Null Count  Dtype  \n",
            "---  ------               --------------  -----  \n",
            " 0   Building Type        1000 non-null   str    \n",
            " 1   Square Footage       1000 non-null   int64  \n",
            " 2   Number of Occupants  1000 non-null   int64  \n",
            " 3   Appliances Used      1000 non-null   int64  \n",
            " 4   Average Temperature  1000 non-null   float64\n",
            " 5   Day of Week          1000 non-null   str    \n",
            " 6   Energy Consumption   1000 non-null   float64\n",
            "dtypes: float64(2), int64(3), str(2)\n",
            "memory usage: 54.8 KB\n"
          ]
        },
        {
          "data": {
            "text/plain": [
              "None"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "text/plain": [
              "Building Type          0.0\n",
              "Square Footage         0.0\n",
              "Number of Occupants    0.0\n",
              "Appliances Used        0.0\n",
              "Average Temperature    0.0\n",
              "Day of Week            0.0\n",
              "Energy Consumption     0.0\n",
              "dtype: float64"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "df = df.drop_duplicates()\n",
        "df = df.dropna()\n",
        "display(df.info())\n",
        "display(df.isna().mean().sort_values(ascending=False))"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "35e99891",
      "metadata": {},
      "source": [
        "Загружаем **тестовую выборку** (`test_energy_data.csv`) — на ней будем считать метрики качества моделей (без использования для обучения)."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 85,
      "id": "c09c6a3a",
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Train: 1000 объектов. Test: 100 объектов.\n"
          ]
        }
      ],
      "source": [
        "# Обучающая выборка (признаки и целевая переменная)\n",
        "df_model = df.dropna(subset=[\"Energy Consumption\"]).copy()\n",
        "X_train = df_model.drop(columns=[\"Energy Consumption\"])\n",
        "y_train = df_model[\"Energy Consumption\"]\n",
        "\n",
        "# Тестовая выборка из файла test_energy_data.csv\n",
        "df_test = pd.read_csv(\"test_energy_data.csv\").dropna(subset=[\"Energy Consumption\"])\n",
        "X_test = df_test.drop(columns=[\"Energy Consumption\"])\n",
        "y_test = df_test[\"Energy Consumption\"]\n",
        "print(\"Train:\", X_train.shape[0], \"объектов. Test:\", X_test.shape[0], \"объектов.\")"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "571cc12d",
      "metadata": {},
      "source": [
        "## Задание 1. Анализ исходных данных. Постановка задачи.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 86,
      "id": "861b82a1",
      "metadata": {},
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 700x400 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 700x400 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# График 1: распределение целевой переменной (энергопотребление)\n",
        "def hist(df, label):\n",
        "    plt.figure(figsize=(7, 4))\n",
        "    sns.histplot(df[\"Energy Consumption\"], bins=50)\n",
        "    plt.title(\"Распределение энергопотребления (\" + label + \")\")\n",
        "    plt.xlabel(\"Energy Consumption\")\n",
        "    plt.show()\n",
        "hist(df_model, \"train_energy_data.csv)\")  \n",
        "hist(df_test, \"test_energy_data.csv)\") \n"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "72db1caa",
      "metadata": {},
      "source": [
        "**Описание графика 1:** Распределение целевой переменной Energy Consumption. Видно, что чаще всего встречается потребление около 4000 единиц\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 87,
      "id": "d75488be",
      "metadata": {},
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 1200x400 with 2 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 1200x400 with 2 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# График 2: зависимость энергопотребления от типа здания и площади\n",
        "def plot_building_and_area(df, label):\n",
        "    fig, axes = plt.subplots(1, 2, figsize=(12, 4))\n",
        "    sns.boxplot(data=df, x=\"Building Type\", y=\"Energy Consumption\", ax=axes[0])\n",
        "    axes[0].set_title(f\"Энергопотребление по типу здания ({label})\")\n",
        "    sns.scatterplot(data=df, x=\"Square Footage\", y=\"Energy Consumption\", alpha=0.4, ax=axes[1])\n",
        "    axes[1].set_title(f\"Энергопотребление от площади ({label})\")\n",
        "    plt.tight_layout()\n",
        "    plt.show()\n",
        "\n",
        "plot_building_and_area(df_model, \"train_energy_data.csv\")\n",
        "plot_building_and_area(df_test, \"test_energy_data.csv\")"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "462cc702",
      "metadata": {},
      "source": [
        "**Описание графика 2:** Слева — зависимость энергопотребления от типа здания (Residential, Commercial, Industrial). Справа — связь между площадью здания и энергопотреблением; \n",
        "Можно заметить, что у жилых помещений потребление меньше, чем у коммерческих, а у коммерческих меньше чем у индустриальных. Также видно, что бОльшая площадь ведёт к бОльшему потреблению."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 88,
      "id": "8837110e",
      "metadata": {},
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 1200x400 with 3 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 1200x400 with 3 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# График 3: среднее энергопотребление по дню недели и тепловая карта корреляций\n",
        "num_cols = [\"Square Footage\", \"Number of Occupants\", \"Appliances Used\", \"Average Temperature\", \"Energy Consumption\"]\n",
        "\n",
        "def plot_day_and_corr(df, label):\n",
        "    fig, axes = plt.subplots(1, 2, figsize=(12, 4))\n",
        "    sns.barplot(data=df, x=\"Day of Week\", y=\"Energy Consumption\", estimator=\"mean\", ax=axes[0])\n",
        "    axes[0].set_title(f\"Среднее энергопотребление: будни vs выходные ({label})\")\n",
        "    sns.heatmap(df[num_cols].corr(), annot=True, fmt=\".2f\", cmap=\"coolwarm\", center=0, ax=axes[1])\n",
        "    axes[1].set_title(f\"Корреляция числовых признаков ({label})\")\n",
        "    plt.tight_layout()\n",
        "    plt.show()\n",
        "\n",
        "plot_day_and_corr(df_model, \"train_energy_data.csv\")\n",
        "plot_day_and_corr(df_test, \"test_energy_data.csv\")"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "e8ade242",
      "metadata": {},
      "source": [
        "**Описание графика 3:** Слева — сравнение среднего энергопотребления в будни и выходные. Справа — корреляционная матрица числовых признаков; видно, какие факторы сильнее связаны с энергопотреблением: площадь, количество проживающих, количество бытовой техники - положительно коррелируют с потреблением. А вот средняя температура - не коррелирует.\n",
        "\n",
        "---\n",
        "\n",
        "### Выводы о качестве датасета\n",
        "\n",
        "- **Очистка и предобработка:** выполнены удаление дубликатов и пропусков; после очистки датасет готов к моделированию.\n",
        "- **Качество:** датасет имеет не случайные данные, видна зависимость энергопотребления от других данных, даже на тестовой выборке."
      ]
    },
    {
      "cell_type": "markdown",
      "id": "c4f56adf",
      "metadata": {},
      "source": [
        "## Задание 2. Построить прогнозную модель для оценки энергопотребления\n",
        "\n",
        "Целевая переменная — **Energy Consumption** (количественная). Используем несколько моделей для сравнения точности на train и test."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 89,
      "id": "8479ddf7",
      "metadata": {},
      "outputs": [
        {
          "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>model</th>\n",
              "      <th>split</th>\n",
              "      <th>MAE</th>\n",
              "      <th>RMSE</th>\n",
              "      <th>R2</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>LinearRegression</td>\n",
              "      <td>train</td>\n",
              "      <td>0.011573</td>\n",
              "      <td>0.013650</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>LinearRegression</td>\n",
              "      <td>test</td>\n",
              "      <td>0.012162</td>\n",
              "      <td>0.014197</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>RandomForest</td>\n",
              "      <td>train</td>\n",
              "      <td>34.482342</td>\n",
              "      <td>43.957397</td>\n",
              "      <td>0.997780</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>RandomForest</td>\n",
              "      <td>test</td>\n",
              "      <td>93.290891</td>\n",
              "      <td>118.888277</td>\n",
              "      <td>0.979403</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>GradientBoosting</td>\n",
              "      <td>train</td>\n",
              "      <td>39.154710</td>\n",
              "      <td>50.360767</td>\n",
              "      <td>0.997085</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>GradientBoosting</td>\n",
              "      <td>test</td>\n",
              "      <td>65.365958</td>\n",
              "      <td>83.840513</td>\n",
              "      <td>0.989757</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "              model  split        MAE        RMSE        R2\n",
              "0  LinearRegression  train   0.011573    0.013650  1.000000\n",
              "1  LinearRegression   test   0.012162    0.014197  1.000000\n",
              "2      RandomForest  train  34.482342   43.957397  0.997780\n",
              "3      RandomForest   test  93.290891  118.888277  0.979403\n",
              "4  GradientBoosting  train  39.154710   50.360767  0.997085\n",
              "5  GradientBoosting   test  65.365958   83.840513  0.989757"
            ]
          },
          "execution_count": 89,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Признаки для препроцессинга (по обучающей выборке)\n",
        "cat_cols = X_train.select_dtypes(include=[\"object\", \"string\"]).columns.tolist()\n",
        "num_cols = X_train.select_dtypes(exclude=[\"object\", \"string\"]).columns.tolist()\n",
        "\n",
        "preprocess = ColumnTransformer(\n",
        "    transformers=[\n",
        "        (\"num\", Pipeline([\n",
        "            (\"imputer\", SimpleImputer(strategy=\"median\"))\n",
        "        ]), num_cols),\n",
        "        (\"cat\", Pipeline([\n",
        "            (\"imputer\", SimpleImputer(strategy=\"most_frequent\")),\n",
        "            (\"onehot\", OneHotEncoder(handle_unknown=\"ignore\"))\n",
        "        ]), cat_cols)\n",
        "    ]\n",
        ")\n",
        "\n",
        "models = {\n",
        "    \"LinearRegression\": LinearRegression(),\n",
        "    \"RandomForest\": RandomForestRegressor(n_estimators=200, random_state=42),\n",
        "    \"GradientBoosting\": GradientBoostingRegressor(random_state=42)\n",
        "}\n",
        "\n",
        "def evaluate_models(X_tr, y_tr, X_te, y_te, models):\n",
        "    \"\"\"Обучает модели на X_tr, y_tr; считает метрики на обучающей и на тестовой (X_te, y_te) выборках.\"\"\"\n",
        "    rows = []\n",
        "    for name, model in models.items():\n",
        "        pipe = Pipeline([\n",
        "            (\"preprocess\", preprocess),\n",
        "            (\"model\", model)\n",
        "        ])\n",
        "        pipe.fit(X_tr, y_tr)\n",
        "        for split, (X_s, y_s) in {\n",
        "            \"train\": (X_tr, y_tr),\n",
        "            \"test\": (X_te, y_te)\n",
        "        }.items():\n",
        "            pred = pipe.predict(X_s)\n",
        "            rows.append({\n",
        "                \"model\": name,\n",
        "                \"split\": split,\n",
        "                \"MAE\": mean_absolute_error(y_s, pred),\n",
        "                \"RMSE\": np.sqrt(mean_squared_error(y_s, pred)),\n",
        "                \"R2\": r2_score(y_s, pred)\n",
        "            })\n",
        "    return pd.DataFrame(rows)\n",
        "\n",
        "# Обучаем на train_energy_data.csv, оцениваем на train и на test_energy_data.csv\n",
        "results_before = evaluate_models(X_train, y_train, X_test, y_test, models)\n",
        "results_before"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 90,
      "id": "1fd412bc",
      "metadata": {},
      "outputs": [
        {
          "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 tr th {\n",
              "        text-align: left;\n",
              "    }\n",
              "\n",
              "    .dataframe thead tr:last-of-type th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th></th>\n",
              "      <th colspan=\"2\" halign=\"left\">MAE</th>\n",
              "      <th colspan=\"2\" halign=\"left\">R2</th>\n",
              "      <th colspan=\"2\" halign=\"left\">RMSE</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>split</th>\n",
              "      <th>test</th>\n",
              "      <th>train</th>\n",
              "      <th>test</th>\n",
              "      <th>train</th>\n",
              "      <th>test</th>\n",
              "      <th>train</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>model</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>GradientBoosting</th>\n",
              "      <td>65.365958</td>\n",
              "      <td>39.154710</td>\n",
              "      <td>0.989757</td>\n",
              "      <td>0.997085</td>\n",
              "      <td>83.840513</td>\n",
              "      <td>50.360767</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>LinearRegression</th>\n",
              "      <td>0.012162</td>\n",
              "      <td>0.011573</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.014197</td>\n",
              "      <td>0.013650</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>RandomForest</th>\n",
              "      <td>93.290891</td>\n",
              "      <td>34.482342</td>\n",
              "      <td>0.979403</td>\n",
              "      <td>0.997780</td>\n",
              "      <td>118.888277</td>\n",
              "      <td>43.957397</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                        MAE                   R2                  RMSE  \\\n",
              "split                  test      train      test     train        test   \n",
              "model                                                                    \n",
              "GradientBoosting  65.365958  39.154710  0.989757  0.997085   83.840513   \n",
              "LinearRegression   0.012162   0.011573  1.000000  1.000000    0.014197   \n",
              "RandomForest      93.290891  34.482342  0.979403  0.997780  118.888277   \n",
              "\n",
              "                             \n",
              "split                 train  \n",
              "model                        \n",
              "GradientBoosting  50.360767  \n",
              "LinearRegression   0.013650  \n",
              "RandomForest      43.957397  "
            ]
          },
          "execution_count": 90,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Таблица результатов (train / test)\n",
        "pivot_before = results_before.pivot_table(index=\"model\", columns=\"split\", values=[\"MAE\", \"RMSE\", \"R2\"])\n",
        "pivot_before"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 91,
      "id": "eabdd5b5",
      "metadata": {},
      "outputs": [
        {
          "data": {
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dagwdOtQc+82bN42lS5cajRo1MpKSkgzDMIzdu3cbvr6+xieffGKcOHHCWLhwoeHj42McPHjQMIy7j0NrjnPm53n7s7BDhw5GbGysERMTYzRs2ND48MMPDcMwjF9//dWoVauWMXv2bOP48ePG9OnTDS8vL4vngvxFDiWHWoP8Sf7MDvmT/FkUkT/Jn9YihxadHEr+JH9StM3EmoRZs2ZN49q1a+bt7du3N+bOnWsYhmF0797d+PTTTy0e36FDB+PTTz81MjIyjEWLFhkXLlwwb9u1a5dRs2ZNwzD+Gig7d+40b789kGrXrm3+8/b2Npo3b25OQoZhGNOmTTMGDBhg0W94eLh5XdeuXY3p06ebt125csUICAiwSJiTJ082b1+1apXRoUMHi/19+umn5nV9+vQxevXqZSQnJxuGYRjx8fFGfHy8YRiG0a5dO2PYsGFGWlqaYRiG8fPPPxtnzpwxDMMyYbZv396YOnWqRR9dunQxpkyZYo7pgw8+MG/bunWr4evra9iLJ5980qhVq5b5uNSqVcsIDAw03nrrLeOPP/4wrl+/bixYsMCcwAzDMJYvX240b97cMIy/ju3Ro0fN2/v372+88847hmEYxsCBA43hw4ebt/3xxx+Gn5+fsWbNGiMjI8OoV6+esWLFCvP2tLQ044knnjCWL19uGMatMZ15e6dOnYy3337bvDxp0iSjV69eFrFkHme1a9c23nrrLcMwbr32AQEB5v/xMwzD2Llzp+Hj42MkJSUZa9asMby8vIyUlBTz9qZNmxrbtm0zL6enpxsNGjQwtm3bZvz888+Gp6en8d133xmGcSsZfPPNN+bxlN3/jNja/v37DU9PT+PkyZPmdd99953F69WmTZtsX4s1a9YYcXFx5uXjx48bnp6exvnz542jR48anp6exrlz58zbJ06cmG3S3L17t9GgQQPDZDKZ227bts2oV6+euZ+7fT6tWbPGvF/DMIyhQ4caPj4+Fp8tnp6exieffGJu079/f+ONN96weC1ef/11Y/Dgwfcch9Yc5+yS5o4dO8z7ff/9942ePXsahmEYU6dONZ5//nmLmLp06cKXThsih5JDrUH+JH+SP8mfuIX8Sf60Fjm06ORQ8udfimr+ZE7bf8jDw0MlS5Y0L5csWVLp6emSpOPHj2vy5Mn68MMPzdtTU1N16tQpOTg4qHv37tqwYYP279+vkydP6tChQ8rIyLDYf6VKlbL0uW7dOvP+x4wZo+bNm+uFF14wbz9x4oR27NihwMBA87qbN2+qatWqkqS4uDiFhYWZt913333mbdn1e+LECR05csRifyaTyXwpzEsvvaR+/fqpYcOGatiwoVq2bKl27dpJkl577TWNGDFCW7ZsUdOmTdWmTRv5+PhkeU7Hjx9X//79LdbVrl3bfOmGJD366KPmf5csWdJ8iYu9GDRokJ5++mldv35dM2fO1Llz5/Tmm2/qgQcekCR1795d69at06FDh3TixAkdPnxYZcuWtdhHlSpVzP/++1jq1q2bedsDDzxgnmT8999/15UrVxQQEGDeXrx4cdWqVcvi9cs8Kbmrq6vFMXZ1dbW4DEb6a5zd5u7ubo7l0Ucf1X333WfeVqdOHaWnp5svpfDw8JCrq6ukWxOmX7x4UYMHD1axYn/NxHLjxg2dOnVKTz75pJo1a6aePXuqatWqat68uTp37iw3N7fsX2g7cPuSlKtXr5rXBQYGml+zzZs3a/ny5ZIsXwtJat++vbZu3apVq1bpxIkT+vnnnyXdek/Fx8fr/vvvV8WKFc3t/fz8FBUVlSWG48eP68qVKwoKCjKvy8jI0I0bN3T58mVz33f6fMpOSEiI3nrrLUm3Pquio6MVHh6u0qVLKzQ0NMs4vP2816xZc89x2LVr1391nP/+3rj9/o+Li5Ofn59F29q1a+vPP//M0X5hW+RQcqhE/iR/kj/Jn7AW+ZP8eRs5tGjkUPLnX4pq/qRo+w/9fb4N6a8Jlk0mk0aMGKGGDRtabC9ZsqQyMjLUq1cvXb16VW3atFFISIhu3rypAQMGWLR1cXHJsv/bg6dKlSq6//779cILL+jBBx9Uz549JUnp6elq166d+vTpY/E4J6dbh9nR0THLJNB/X87cb3p6uho2bKjRo0dn+xo0bNhQO3fu1LZt2/T1119r9OjR+vbbbzVlyhQ9++yzatiwobZu3aqvv/5agwYN0n/+8x8NHjz4ns/TZDJZ/A+Evd/l08PDw3xsPvroI3Xq1En9+vXTypUrlZaWpk6dOumBBx5QSEiI2rZtqxMnTmjhwoUW+/j7eMp8XP5+jG6/Htm9dlLW1y/zfFOSLJJXdjJ/SGV2p2OV+b+Z29xe99FHH2X5H7P77rtPDg4Omj9/vg4cOKBt27Zpy5Yt+uyzz/TZZ5/J29v7rjHayu333k8//SR/f39Jkpubm/k18/DwMLf9++s1ZMgQ/fTTT3ruuefUvXt3lStXTl27djVvv9Nx/rv09HRVq1Yty9xS0l93WL3b51N2SpQoYXHcPT099csvv2jp0qUKDQ3N9thnZGQoIyPjnuPw3x7nO70OOfk8g/0ih5JDJfJn5v+SP8mft5E/cTfkT/LnbeTQopFDyZ9/Kar5kxuR5YGqVavq4sWLqlKlivlv3rx5iomJUXx8vPbt26dFixapT58+atasmX777TdJ1h3wOnXq6Pnnn9f06dN17tw5c7+nT5+26Hfbtm363//+J0mqUaOG+dcVSUpKStLp06fv+jxOnjypypUrm/cXExOjJUuWSLo1ofzPP/+sDh066KOPPlJ4eLh5cuhp06bp999/V/fu3TV//ny9/vrrFhNHZ+4jNjbWYl1sbGyWD9iCwtnZWe+9955++eUXLVq0SD/88IN+++03ffrpp3rttdf0+OOP6/z58zk+1o899pgOHjxoXs58zEqVKqWyZcsqJibGvP3mzZv6+eef8+T1q1q1qk6dOmUxEXdMTIycnJz0yCOPZGlfunRpeXh4KCEhwTx+HnroIU2ePFknT57U8ePHNXHiRPn7+2vw4MFav369HnroIX3zzTe5HntucXJyUseOHbV48WLzDQ8yu9OE+klJSfrqq680bdo0DRo0SE899ZT5FznDMOTp6ak///zT4v34yy+/ZLuvqlWr6vz58ypTpoz5dT179qxmzJghBweHez6HnLS5Hdft//HK7n36008/qWrVqvcch3l1nB977DGLzzNJWZZRMJFDi2YOJX/+hfz5F/In+RM5R/4smvlTIodmVthyKPnzL0U1f1K0/ZsDBw5o165dFn8pKSlW7aNnz55avHix1q1bp19//VWTJ0/Wxo0bVb16dZUuXVrFihXT+vXrde7cOUVFRZnvYvn3SwTu5f/+7//k7u6uDz74QJL0/PPP69ChQ5o2bZpOnTql//3vf/rwww/Np7z36NFDn376qTZv3qzjx49rxIgRSk5OvuOb6Nlnn9WNGzc0evRoHT9+XDt37tSECRPMv+ZcvHhR7777rmJiYnTq1Clt2rTJfPnJiRMn9O677+rIkSM6duyYdu7cme2lKa+88oqWLl2qdevW6eTJk5oyZYqOHDmiTp06WfVa2BN/f3916tRJc+bMUenSpZWcnKytW7fq7NmzWr16tZYtW5bjY/3iiy9q48aNWrVqlY4fP67Ro0frxo0b5u2vvPKKZsyYoe3bt+v48eMaNWqUUlNT1aZNm1x/Xo0aNdLDDz+sIUOGKC4uTt9//73Gjx+vtm3bZnsny9vxTZ8+Xdu3b9epU6f0zjvvaP/+/apWrZpKly6t5cuXa86cOTpz5oy+/vprnTt3zjxO3N3ddeLECYsEbQ8GDhyocuXKqVu3boqKitKZM2d04MABjRo1SjNmzLC4bOQ2Z2dnubm5afPmzTp79qy++eYb811509LSVL16dTVs2FAjRozQkSNHtHXrVi1dujTb/hs3bqxKlSrp7bffVlxcnH788UeNGjVKbm5uWX7Rzo6bm5v+/PNPnTp1ynzJyo0bN5SQkKCEhARdunRJGzZs0P/+9z+1bt1a0q3juGnTJi1evFinTp3SokWLtGXLFnXv3t28/U7jMK+Oc5cuXRQTE6OIiAidPHlS8+bN048//pjj/ylA3iCH/oUcaj3y51/In7eQP8mfRQX58y/kz3+GHPqXwpZDyZ9FO38yPcLfTJkyJcu67H6du5s2bdooMTFRM2bMUGJiomrUqKG5c+ea58UZO3asZs+erQ8//FBVq1bVO++8o6FDh+rw4cMqV65cjvspXbq03njjDb3zzjvavXu3Hn/8cc2bN09TpkzRxx9/rAoVKmjYsGF69tlnJUnPPPOMTp8+rTFjxig1NVVdu3ZVpUqV7nj6d8mSJbVgwQK9//77at++vflymN69e0u6lbCvXbumvn37Kjk5WXXr1tXkyZPNz3HcuHHq0aOH0tPT1axZM40cOfKur1VCQoK8vb21cOFCVa9e3ZqX3O4MHjxYmzZt0vLly9W/f3+NGzdOqamp8vLy0ujRozVy5Mg7/iqWWXBwsMLDwzV9+nT98ccf6tixo8Up/b169VJSUpJGjRqlpKQkBQYGasmSJSpTpkyuPydHR0fNmTNH48ePV5cuXVSiRAm1a9dOb7zxxh0f8+qrr+r69esaPXq0kpKSVKtWLX388cfmOYlmzpypKVOmaN68efLw8NAbb7yhxo0bS7o1D9OUKVN06tQpzZo1K9efzz/l5uamJUuWaPHixZozZ45Onz4tZ2dn+fv7a+bMmWrRooUiIyMtHuPs7KzJkydr4sSJWrJkiSpXrqy+fftq+vTp+uWXX1S9enVNmzZNo0aNUrdu3VSxYkX16NEjy36kW8dh7ty55uPg7u6uVq1aaejQoTmKv0GDBqpSpYratWunzz77TJK0ceNGbdy4UdKtX3MffPBB9e7dW6+99pokKSAgQJMmTdLMmTM1efJkVa1aVdOnTzdffnevcZjT49yjR48cH4dKlSppxowZmjhxombMmKFGjRq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            "text/plain": [
              "<Figure size 1400x400 with 3 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# Визуализация метрик на тесте\n",
        "test_before = results_before[results_before[\"split\"] == \"test\"]\n",
        "fig, axes = plt.subplots(1, 3, figsize=(14, 4))\n",
        "sns.barplot(data=test_before, x=\"model\", y=\"MAE\", ax=axes[0])\n",
        "sns.barplot(data=test_before, x=\"model\", y=\"RMSE\", ax=axes[1])\n",
        "sns.barplot(data=test_before, x=\"model\", y=\"R2\", ax=axes[2])\n",
        "axes[0].set_title(\"MAE (test)\")\n",
        "axes[1].set_title(\"RMSE (test)\")\n",
        "axes[2].set_title(\"R2 (test)\")\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "23888437",
      "metadata": {},
      "source": [
        "### Почему выбраны эти метрики\n",
        "\n",
        "- **MAE** (Mean Absolute Error) — средняя абсолютная ошибка в тех же единицах, что и энергопотребление; интерпретируема и устойчива к выбросам.\n",
        "- **RMSE** (Root Mean Squared Error) — корень из средней квадратичной ошибки; сильнее штрафует большие ошибки, полезна для оценки риска крупных промахов.\n",
        "- **R2** (коэффициент детерминации) — доля объяснённой дисперсии: 0 означает, что модель не лучше предсказания средним, 1 — полное совпадение с целевой переменной."
      ]
    },
    {
      "cell_type": "markdown",
      "id": "eadb5756",
      "metadata": {},
      "source": [
        "## Задание 3. Добавление 20 новых записей и анализ изменений точности\n",
        "\n",
        "Добавляем 20 новых записей. Признаки генерируются по следующему **принципу**:\n",
        "- **Building Type**, **Day of Week** — случайный выбор из тех же категорий, что и в исходных данных (равновероятно или пропорционально).\n",
        "- **Square Footage**, **Number of Occupants**, **Appliances Used**, **Average Temperature** — случайные значения из диапазонов, совпадающих с минимумом и максимумом по обучающей выборке (равномерное распределение), чтобы новые точки не выходили за пределы уже наблюдаемых.\n",
        "- **Energy Consumption** — для новых записей задаём по упрощённой формуле, согласованной с данными: базовая составляющая от площади и числа жильцов плюс случайный шум в диапазоне стандартного отклонения целевой переменной, чтобы новые строки были «правдоподобны» и не ломали распределение."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 92,
      "id": "357262bb",
      "metadata": {},
      "outputs": [
        {
          "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>Building Type</th>\n",
              "      <th>Square Footage</th>\n",
              "      <th>Number of Occupants</th>\n",
              "      <th>Appliances Used</th>\n",
              "      <th>Average Temperature</th>\n",
              "      <th>Day of Week</th>\n",
              "      <th>Energy Consumption</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Industrial</td>\n",
              "      <td>47560.463166</td>\n",
              "      <td>73</td>\n",
              "      <td>30</td>\n",
              "      <td>13.94</td>\n",
              "      <td>Weekend</td>\n",
              "      <td>6346.46</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Industrial</td>\n",
              "      <td>3348.819232</td>\n",
              "      <td>72</td>\n",
              "      <td>46</td>\n",
              "      <td>10.07</td>\n",
              "      <td>Weekend</td>\n",
              "      <td>4607.10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Residential</td>\n",
              "      <td>15600.823765</td>\n",
              "      <td>52</td>\n",
              "      <td>22</td>\n",
              "      <td>17.31</td>\n",
              "      <td>Weekday</td>\n",
              "      <td>3895.37</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Industrial</td>\n",
              "      <td>5039.310304</td>\n",
              "      <td>62</td>\n",
              "      <td>19</td>\n",
              "      <td>34.57</td>\n",
              "      <td>Weekend</td>\n",
              "      <td>4711.79</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Residential</td>\n",
              "      <td>43072.873888</td>\n",
              "      <td>68</td>\n",
              "      <td>23</td>\n",
              "      <td>10.38</td>\n",
              "      <td>Weekday</td>\n",
              "      <td>5582.57</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Commercial</td>\n",
              "      <td>1349.323611</td>\n",
              "      <td>23</td>\n",
              "      <td>12</td>\n",
              "      <td>27.09</td>\n",
              "      <td>Weekday</td>\n",
              "      <td>3261.35</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Residential</td>\n",
              "      <td>2260.065318</td>\n",
              "      <td>91</td>\n",
              "      <td>13</td>\n",
              "      <td>26.57</td>\n",
              "      <td>Weekend</td>\n",
              "      <td>4543.40</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>Commercial</td>\n",
              "      <td>9698.649718</td>\n",
              "      <td>96</td>\n",
              "      <td>38</td>\n",
              "      <td>33.48</td>\n",
              "      <td>Weekend</td>\n",
              "      <td>5503.54</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>Commercial</td>\n",
              "      <td>30118.381252</td>\n",
              "      <td>92</td>\n",
              "      <td>5</td>\n",
              "      <td>14.94</td>\n",
              "      <td>Weekend</td>\n",
              "      <td>5043.68</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>Residential</td>\n",
              "      <td>27240.759949</td>\n",
              "      <td>59</td>\n",
              "      <td>48</td>\n",
              "      <td>25.19</td>\n",
              "      <td>Weekend</td>\n",
              "      <td>5990.45</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>Residential</td>\n",
              "      <td>15206.873301</td>\n",
              "      <td>17</td>\n",
              "      <td>1</td>\n",
              "      <td>20.61</td>\n",
              "      <td>Weekday</td>\n",
              "      <td>2556.43</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>Industrial</td>\n",
              "      <td>10390.171931</td>\n",
              "      <td>71</td>\n",
              "      <td>39</td>\n",
              "      <td>25.16</td>\n",
              "      <td>Weekday</td>\n",
              "      <td>4978.12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>Commercial</td>\n",
              "      <td>32747.294910</td>\n",
              "      <td>91</td>\n",
              "      <td>42</td>\n",
              "      <td>21.26</td>\n",
              "      <td>Weekday</td>\n",
              "      <td>6544.77</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>Commercial</td>\n",
              "      <td>33481.203544</td>\n",
              "      <td>59</td>\n",
              "      <td>14</td>\n",
              "      <td>24.05</td>\n",
              "      <td>Weekend</td>\n",
              "      <td>5094.18</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>Industrial</td>\n",
              "      <td>48598.530860</td>\n",
              "      <td>85</td>\n",
              "      <td>36</td>\n",
              "      <td>15.94</td>\n",
              "      <td>Weekday</td>\n",
              "      <td>6667.79</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>Residential</td>\n",
              "      <td>2113.764653</td>\n",
              "      <td>64</td>\n",
              "      <td>16</td>\n",
              "      <td>22.73</td>\n",
              "      <td>Weekday</td>\n",
              "      <td>3928.83</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>Commercial</td>\n",
              "      <td>12884.259932</td>\n",
              "      <td>41</td>\n",
              "      <td>38</td>\n",
              "      <td>15.76</td>\n",
              "      <td>Weekday</td>\n",
              "      <td>4165.87</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>Commercial</td>\n",
              "      <td>46521.462839</td>\n",
              "      <td>81</td>\n",
              "      <td>32</td>\n",
              "      <td>31.78</td>\n",
              "      <td>Weekend</td>\n",
              "      <td>7000.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>Commercial</td>\n",
              "      <td>27223.462414</td>\n",
              "      <td>80</td>\n",
              "      <td>44</td>\n",
              "      <td>17.98</td>\n",
              "      <td>Weekend</td>\n",
              "      <td>5941.62</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>Commercial</td>\n",
              "      <td>41000.195983</td>\n",
              "      <td>86</td>\n",
              "      <td>1</td>\n",
              "      <td>22.79</td>\n",
              "      <td>Weekday</td>\n",
              "      <td>5669.67</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   Building Type  Square Footage  Number of Occupants  Appliances Used  \\\n",
              "0     Industrial    47560.463166                   73               30   \n",
              "1     Industrial     3348.819232                   72               46   \n",
              "2    Residential    15600.823765                   52               22   \n",
              "3     Industrial     5039.310304                   62               19   \n",
              "4    Residential    43072.873888                   68               23   \n",
              "5     Commercial     1349.323611                   23               12   \n",
              "6    Residential     2260.065318                   91               13   \n",
              "7     Commercial     9698.649718                   96               38   \n",
              "8     Commercial    30118.381252                   92                5   \n",
              "9    Residential    27240.759949                   59               48   \n",
              "10   Residential    15206.873301                   17                1   \n",
              "11    Industrial    10390.171931                   71               39   \n",
              "12    Commercial    32747.294910                   91               42   \n",
              "13    Commercial    33481.203544                   59               14   \n",
              "14    Industrial    48598.530860                   85               36   \n",
              "15   Residential     2113.764653                   64               16   \n",
              "16    Commercial    12884.259932                   41               38   \n",
              "17    Commercial    46521.462839                   81               32   \n",
              "18    Commercial    27223.462414                   80               44   \n",
              "19    Commercial    41000.195983                   86                1   \n",
              "\n",
              "    Average Temperature Day of Week  Energy Consumption  \n",
              "0                 13.94     Weekend             6346.46  \n",
              "1                 10.07     Weekend             4607.10  \n",
              "2                 17.31     Weekday             3895.37  \n",
              "3                 34.57     Weekend             4711.79  \n",
              "4                 10.38     Weekday             5582.57  \n",
              "5                 27.09     Weekday             3261.35  \n",
              "6                 26.57     Weekend             4543.40  \n",
              "7                 33.48     Weekend             5503.54  \n",
              "8                 14.94     Weekend             5043.68  \n",
              "9                 25.19     Weekend             5990.45  \n",
              "10                20.61     Weekday             2556.43  \n",
              "11                25.16     Weekday             4978.12  \n",
              "12                21.26     Weekday             6544.77  \n",
              "13                24.05     Weekend             5094.18  \n",
              "14                15.94     Weekday             6667.79  \n",
              "15                22.73     Weekday             3928.83  \n",
              "16                15.76     Weekday             4165.87  \n",
              "17                31.78     Weekend             7000.00  \n",
              "18                17.98     Weekend             5941.62  \n",
              "19                22.79     Weekday             5669.67  "
            ]
          },
          "execution_count": 92,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Генерация 20 новых записей\n",
        "np.random.seed(42)\n",
        "n_new = 20\n",
        "\n",
        "building_types = df[\"Building Type\"].unique()\n",
        "day_of_week = df[\"Day of Week\"].unique()\n",
        "sq_min, sq_max = df[\"Square Footage\"].min(), df[\"Square Footage\"].max()\n",
        "occ_min, occ_max = df[\"Number of Occupants\"].min(), df[\"Number of Occupants\"].max()\n",
        "app_min, app_max = df[\"Appliances Used\"].min(), df[\"Appliances Used\"].max()\n",
        "temp_min, temp_max = df[\"Average Temperature\"].min(), df[\"Average Temperature\"].max()\n",
        "y_mean, y_std = df[\"Energy Consumption\"].mean(), df[\"Energy Consumption\"].std()\n",
        "\n",
        "new_rows = []\n",
        "for _ in range(n_new):\n",
        "    bt = np.random.choice(building_types)\n",
        "    dow = np.random.choice(day_of_week)\n",
        "    sq = np.random.uniform(sq_min, sq_max)\n",
        "    occ = int(np.random.uniform(occ_min, occ_max + 1))\n",
        "    app = int(np.random.uniform(app_min, app_max + 1))\n",
        "    temp = np.random.uniform(temp_min, temp_max)\n",
        "    # Правдоподобное энергопотребление: линейная комбинация признаков + шум в масштабе y_std\n",
        "    energy = 0.05 * sq + 20 * occ + 30 * app + 50 * temp + np.random.normal(y_mean * 0.2, y_std * 0.3)\n",
        "    energy = max(1500, min(7000, energy))  # в разумных границах\n",
        "    new_rows.append({\n",
        "        \"Building Type\": bt, \"Square Footage\": sq, \"Number of Occupants\": occ,\n",
        "        \"Appliances Used\": app, \"Average Temperature\": round(temp, 2), \"Day of Week\": dow,\n",
        "        \"Energy Consumption\": round(energy, 2)\n",
        "    })\n",
        "\n",
        "df_new = pd.DataFrame(new_rows)\n",
        "df_new"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 93,
      "id": "53f17cc6",
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Размер до: 1000 после: 1020\n"
          ]
        }
      ],
      "source": [
        "# Объединяем исходные данные и 20 новых записей\n",
        "df_extended = pd.concat([df_model, df_new], ignore_index=True)\n",
        "print(\"Размер до:\", len(df_model), \"после:\", len(df_extended))\n",
        "X_ext = df_extended.drop(columns=[\"Energy Consumption\"])\n",
        "y_ext = df_extended[\"Energy Consumption\"]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 94,
      "id": "5bea9f00",
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
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              "        vertical-align: middle;\n",
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              "\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>model</th>\n",
              "      <th>split</th>\n",
              "      <th>MAE</th>\n",
              "      <th>RMSE</th>\n",
              "      <th>R2</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>LinearRegression</td>\n",
              "      <td>train</td>\n",
              "      <td>35.939594</td>\n",
              "      <td>138.575984</td>\n",
              "      <td>0.978559</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>LinearRegression</td>\n",
              "      <td>test</td>\n",
              "      <td>19.108061</td>\n",
              "      <td>23.788196</td>\n",
              "      <td>0.999175</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>RandomForest</td>\n",
              "      <td>train</td>\n",
              "      <td>40.832184</td>\n",
              "      <td>72.347452</td>\n",
              "      <td>0.994156</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>RandomForest</td>\n",
              "      <td>test</td>\n",
              "      <td>91.188920</td>\n",
              "      <td>117.337753</td>\n",
              "      <td>0.979936</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>GradientBoosting</td>\n",
              "      <td>train</td>\n",
              "      <td>56.667122</td>\n",
              "      <td>101.997400</td>\n",
              "      <td>0.988384</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>GradientBoosting</td>\n",
              "      <td>test</td>\n",
              "      <td>74.311407</td>\n",
              "      <td>97.239319</td>\n",
              "      <td>0.986221</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "              model  split        MAE        RMSE        R2\n",
              "0  LinearRegression  train  35.939594  138.575984  0.978559\n",
              "1  LinearRegression   test  19.108061   23.788196  0.999175\n",
              "2      RandomForest  train  40.832184   72.347452  0.994156\n",
              "3      RandomForest   test  91.188920  117.337753  0.979936\n",
              "4  GradientBoosting  train  56.667122  101.997400  0.988384\n",
              "5  GradientBoosting   test  74.311407   97.239319  0.986221"
            ]
          },
          "execution_count": 94,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Обучаем модели на расширенной выборке и собираем метрики\n",
        "results_after = evaluate_models(X_ext, y_ext, X_test, y_test, models)\n",
        "results_after"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 95,
      "id": "90d16f0d",
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
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              "\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>MAE_before</th>\n",
              "      <th>MAE_after</th>\n",
              "      <th>RMSE_before</th>\n",
              "      <th>RMSE_after</th>\n",
              "      <th>R2_before</th>\n",
              "      <th>R2_after</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>model</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>LinearRegression</th>\n",
              "      <td>0.012162</td>\n",
              "      <td>19.108061</td>\n",
              "      <td>0.014197</td>\n",
              "      <td>23.788196</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.999175</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>RandomForest</th>\n",
              "      <td>93.290891</td>\n",
              "      <td>91.188920</td>\n",
              "      <td>118.888277</td>\n",
              "      <td>117.337753</td>\n",
              "      <td>0.979403</td>\n",
              "      <td>0.979936</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>GradientBoosting</th>\n",
              "      <td>65.365958</td>\n",
              "      <td>74.311407</td>\n",
              "      <td>83.840513</td>\n",
              "      <td>97.239319</td>\n",
              "      <td>0.989757</td>\n",
              "      <td>0.986221</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                  MAE_before  MAE_after  RMSE_before  RMSE_after  R2_before  \\\n",
              "model                                                                         \n",
              "LinearRegression    0.012162  19.108061     0.014197   23.788196   1.000000   \n",
              "RandomForest       93.290891  91.188920   118.888277  117.337753   0.979403   \n",
              "GradientBoosting   65.365958  74.311407    83.840513   97.239319   0.989757   \n",
              "\n",
              "                  R2_after  \n",
              "model                       \n",
              "LinearRegression  0.999175  \n",
              "RandomForest      0.979936  \n",
              "GradientBoosting  0.986221  "
            ]
          },
          "execution_count": 95,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Сравнение метрик на тесте (test_energy_data.csv): ДО и ПОСЛЕ добавления 20 записей\n",
        "# Оба варианта оценивались на одной и той же тестовой выборке из файла\n",
        "tb = results_before[results_before[\"split\"] == \"test\"].set_index(\"model\")\n",
        "ta = results_after[results_after[\"split\"] == \"test\"].set_index(\"model\")\n",
        "comparison = pd.DataFrame({\n",
        "    \"MAE_before\": tb[\"MAE\"],\n",
        "    \"MAE_after\": ta[\"MAE\"],\n",
        "    \"RMSE_before\": tb[\"RMSE\"],\n",
        "    \"RMSE_after\": ta[\"RMSE\"],\n",
        "    \"R2_before\": tb[\"R2\"],\n",
        "    \"R2_after\": ta[\"R2\"]\n",
        "})\n",
        "comparison"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "a5852867",
      "metadata": {},
      "source": [
        "### Анализ изменений в точности моделей\n",
        "\n",
        "- Добавление 20 новых записей, сгенерированных в тех же диапазонах признаков и с правдоподобной целевой переменной, все же снижает качество работы моделей: модель которая не использует в обучении сгенерированные данные, показывает меньшую ошибку на тестовых данных, но эффект выражен несильно, т.к. данных совсем мало.\n",
        "- Для корректного сравнения метрики считаются на одной и той же тестовой выборке из файла `test_energy_data.csv`."
      ]
    }
  ],
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