diff --git a/lab_4/lab4.ipynb b/lab_4/lab4.ipynb
new file mode 100644
index 0000000..3cc2a4b
--- /dev/null
+++ b/lab_4/lab4.ipynb
@@ -0,0 +1,957 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## **Лабораторная работа №4**\n",
+    "\n",
+    "### **Определение бизнес-целей для решения задач регрессии и классификации**\n",
+    "\n",
+    "**Вариант задания:** Набор данных о ценах на акции Walmart.\n",
+    "\n",
+    "**Бизнес-цели:**\n",
+    "\n",
+    "1. **Регрессия:** Предсказание цены закрытия акции (Close) на основе исторических данных.\n",
+    "\n",
+    "2. **Классификация:** Определение направления изменения цены (повышение или понижение) на следующий день, что можно выразить в бинарной метке (например, 1 — цена повысилась, 0 — снизилась). Метка будет рассчитываться как разница между Close сегодняшнего и завтрашнего дня.\n",
+    "\n",
+    "**Столбцы датасета и их пояснение:**\n",
+    "\n",
+    "*Date* - Дата, на которую относятся данные. Эта характеристика указывает конкретный день, в который происходила торговля акциями Walmart.\n",
+    "\n",
+    "*Open* - Цена открытия. Стоимость акций Walmart в начале торгового дня. Это важный показатель, который показывает, по какой цене начались торги в конкретный день, и часто используется для сравнения с ценой закрытия для определения дневного тренда.\n",
+    "\n",
+    "*High* - Максимальная цена за день. Наибольшая цена, достигнутая акциями Walmart в течение торгового дня. Эта характеристика указывает, какой была самая высокая стоимость акций за день.\n",
+    "\n",
+    "*Low* - Минимальная цена за день. Наименьшая цена, по которой торговались акции Walmart в течение дня.\n",
+    "\n",
+    "*Close* - Цена закрытия. Стоимость акций Walmart в конце торгового дня. Цена закрытия — один из основных показателей, используемых для анализа акций, так как она отображает итоговую стоимость акций за день и часто используется для расчета дневных изменений и трендов на длительных временных периодах.\n",
+    "\n",
+    "*Adj Close* - Скорректированная цена закрытия. Цена закрытия, скорректированная с учетом всех корпоративных действий.\n",
+    "\n",
+    "*Volume* - Объем торгов. Количество акций Walmart, проданных и купленных в течение дня. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "       Date       Open       High        Low      Close  Adj Close    Volume\n",
+      "0  1/3/2000  22.791668  23.000000  21.833332  22.270832  14.469358  25109700\n",
+      "1  1/4/2000  21.833332  21.937500  21.395832  21.437500  13.927947  20235300\n",
+      "2  1/5/2000  21.291668  21.458332  20.729168  21.000000  13.643703  21056100\n",
+      "3  1/6/2000  21.000000  21.520832  20.895832  21.229168  13.792585  19633500\n",
+      "4  1/7/2000  21.500000  22.979168  21.500000  22.833332  14.834813  23930700\n",
+      "Index(['Date', 'Open', 'High', 'Low', 'Close', 'Adj Close', 'Volume'], dtype='object')\n"
+     ]
+    },
+    {
+     "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>Date</th>\n",
+       "      <th>Open</th>\n",
+       "      <th>High</th>\n",
+       "      <th>Low</th>\n",
+       "      <th>Close</th>\n",
+       "      <th>Adj Close</th>\n",
+       "      <th>Volume</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1/3/2000</td>\n",
+       "      <td>22.791668</td>\n",
+       "      <td>23.000000</td>\n",
+       "      <td>21.833332</td>\n",
+       "      <td>22.270832</td>\n",
+       "      <td>14.469358</td>\n",
+       "      <td>25109700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1/4/2000</td>\n",
+       "      <td>21.833332</td>\n",
+       "      <td>21.937500</td>\n",
+       "      <td>21.395832</td>\n",
+       "      <td>21.437500</td>\n",
+       "      <td>13.927947</td>\n",
+       "      <td>20235300</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1/5/2000</td>\n",
+       "      <td>21.291668</td>\n",
+       "      <td>21.458332</td>\n",
+       "      <td>20.729168</td>\n",
+       "      <td>21.000000</td>\n",
+       "      <td>13.643703</td>\n",
+       "      <td>21056100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>1/6/2000</td>\n",
+       "      <td>21.000000</td>\n",
+       "      <td>21.520832</td>\n",
+       "      <td>20.895832</td>\n",
+       "      <td>21.229168</td>\n",
+       "      <td>13.792585</td>\n",
+       "      <td>19633500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>1/7/2000</td>\n",
+       "      <td>21.500000</td>\n",
+       "      <td>22.979168</td>\n",
+       "      <td>21.500000</td>\n",
+       "      <td>22.833332</td>\n",
+       "      <td>14.834813</td>\n",
+       "      <td>23930700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>1/10/2000</td>\n",
+       "      <td>22.416668</td>\n",
+       "      <td>22.500000</td>\n",
+       "      <td>21.875000</td>\n",
+       "      <td>22.416668</td>\n",
+       "      <td>14.564112</td>\n",
+       "      <td>20142900</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>1/11/2000</td>\n",
+       "      <td>22.354168</td>\n",
+       "      <td>22.583332</td>\n",
+       "      <td>21.875000</td>\n",
+       "      <td>22.083332</td>\n",
+       "      <td>14.347544</td>\n",
+       "      <td>14829900</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>1/12/2000</td>\n",
+       "      <td>22.062500</td>\n",
+       "      <td>22.250000</td>\n",
+       "      <td>21.687500</td>\n",
+       "      <td>21.687500</td>\n",
+       "      <td>14.090372</td>\n",
+       "      <td>12255000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>1/13/2000</td>\n",
+       "      <td>22.000000</td>\n",
+       "      <td>22.041668</td>\n",
+       "      <td>21.666668</td>\n",
+       "      <td>21.708332</td>\n",
+       "      <td>14.103909</td>\n",
+       "      <td>15063000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>1/14/2000</td>\n",
+       "      <td>21.333332</td>\n",
+       "      <td>21.979168</td>\n",
+       "      <td>21.333332</td>\n",
+       "      <td>21.500000</td>\n",
+       "      <td>13.968553</td>\n",
+       "      <td>18936600</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>1/18/2000</td>\n",
+       "      <td>21.062500</td>\n",
+       "      <td>22.145832</td>\n",
+       "      <td>21.020832</td>\n",
+       "      <td>21.854168</td>\n",
+       "      <td>14.198661</td>\n",
+       "      <td>19326600</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>1/19/2000</td>\n",
+       "      <td>21.750000</td>\n",
+       "      <td>21.937500</td>\n",
+       "      <td>21.333332</td>\n",
+       "      <td>21.354168</td>\n",
+       "      <td>13.873807</td>\n",
+       "      <td>14459700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>1/20/2000</td>\n",
+       "      <td>21.479168</td>\n",
+       "      <td>21.500000</td>\n",
+       "      <td>20.833332</td>\n",
+       "      <td>21.125000</td>\n",
+       "      <td>13.724912</td>\n",
+       "      <td>17214300</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>1/21/2000</td>\n",
+       "      <td>21.312500</td>\n",
+       "      <td>21.312500</td>\n",
+       "      <td>20.687500</td>\n",
+       "      <td>20.812500</td>\n",
+       "      <td>13.521886</td>\n",
+       "      <td>20857500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>1/24/2000</td>\n",
+       "      <td>21.145832</td>\n",
+       "      <td>21.145832</td>\n",
+       "      <td>19.166668</td>\n",
+       "      <td>19.791668</td>\n",
+       "      <td>12.858650</td>\n",
+       "      <td>23399700</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "         Date       Open       High        Low      Close  Adj Close    Volume\n",
+       "0    1/3/2000  22.791668  23.000000  21.833332  22.270832  14.469358  25109700\n",
+       "1    1/4/2000  21.833332  21.937500  21.395832  21.437500  13.927947  20235300\n",
+       "2    1/5/2000  21.291668  21.458332  20.729168  21.000000  13.643703  21056100\n",
+       "3    1/6/2000  21.000000  21.520832  20.895832  21.229168  13.792585  19633500\n",
+       "4    1/7/2000  21.500000  22.979168  21.500000  22.833332  14.834813  23930700\n",
+       "5   1/10/2000  22.416668  22.500000  21.875000  22.416668  14.564112  20142900\n",
+       "6   1/11/2000  22.354168  22.583332  21.875000  22.083332  14.347544  14829900\n",
+       "7   1/12/2000  22.062500  22.250000  21.687500  21.687500  14.090372  12255000\n",
+       "8   1/13/2000  22.000000  22.041668  21.666668  21.708332  14.103909  15063000\n",
+       "9   1/14/2000  21.333332  21.979168  21.333332  21.500000  13.968553  18936600\n",
+       "10  1/18/2000  21.062500  22.145832  21.020832  21.854168  14.198661  19326600\n",
+       "11  1/19/2000  21.750000  21.937500  21.333332  21.354168  13.873807  14459700\n",
+       "12  1/20/2000  21.479168  21.500000  20.833332  21.125000  13.724912  17214300\n",
+       "13  1/21/2000  21.312500  21.312500  20.687500  20.812500  13.521886  20857500\n",
+       "14  1/24/2000  21.145832  21.145832  19.166668  19.791668  12.858650  23399700"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Date         0\n",
+      "Open         0\n",
+      "High         0\n",
+      "Low          0\n",
+      "Close        0\n",
+      "Adj Close    0\n",
+      "Volume       0\n",
+      "dtype: int64\n"
+     ]
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "\n",
+    "df = pd.read_csv(\"..//static//csv//WMT.csv\").head(15000)\n",
+    "\n",
+    "print(df.head())\n",
+    "print(df.columns)\n",
+    "display(df.head(15))\n",
+    "print(df.isnull().sum())"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### **Выберем три модели для задач регрессии и классификации**\n",
+    "\n",
+    "Сделаем выбор подходящих моделей для решения задач классификации и регрессии на основе анализа данных и целей. \n",
+    "\n",
+    "Для регрессии выберем:\n",
+    "\n",
+    "- LinearRegression\n",
+    "- DecisionTreeRegressor\n",
+    "- GradientBoostingRegressor\n",
+    "\n",
+    "Для классификации выберем:\n",
+    "\n",
+    "- LogisticRegression\n",
+    "- RandomForestClassifier\n",
+    "- GradientBoostingClassifier"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### **Разбиение на выборки и создание ориентира для задач регрессии**\n",
+    "\n",
+    "Мы будем использовать подход к задаче регрессии, где целевой переменной будет выступать цена товара, а другие характеристики, кроме ссылок, выбраны в качестве признаков."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Размер обучающей выборки: (4894, 6)\n",
+      "Размер тестовой выборки: (1224, 6)\n",
+      "Baseline MAE: 9.224148034130094\n",
+      "Baseline MSE: 129.81371036926848\n",
+      "Baseline R²: -0.002482369649123406\n"
+     ]
+    }
+   ],
+   "source": [
+    "from sklearn.model_selection import train_test_split\n",
+    "from sklearn.metrics import mean_absolute_error, mean_squared_error, r2_score\n",
+    "\n",
+    "# Определяем признаки и целевой признак для задачи регрессии\n",
+    "features = ['Date', 'Open', 'High', 'Low', 'Adj Close', 'Volume'] \n",
+    "target = 'Close'  # Целевая переменная\n",
+    "\n",
+    "X_train, X_test, y_train, y_test = train_test_split(df[features], df[target], test_size=0.2, random_state=42)\n",
+    "\n",
+    "print(\"Размер обучающей выборки:\", X_train.shape)\n",
+    "print(\"Размер тестовой выборки:\", X_test.shape)\n",
+    "\n",
+    "baseline_predictions = [y_train.mean()] * len(y_test)\n",
+    "\n",
+    "print('Baseline MAE:', mean_absolute_error(y_test, baseline_predictions))\n",
+    "print('Baseline MSE:', mean_squared_error(y_test, baseline_predictions))\n",
+    "print('Baseline R²:', r2_score(y_test, baseline_predictions))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### **Построение конвейера и обучение моделей для задач регрессии**\n",
+    "\n",
+    "Переделаем характристики под числовые данные и построим конвейер для обучения моделей, а также оценим их качество."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Model: Linear Regression trained.\n",
+      "Model: Decision Tree trained.\n",
+      "Model: Gradient Boosting trained.\n"
+     ]
+    }
+   ],
+   "source": [
+    "from sklearn.model_selection import train_test_split\n",
+    "from sklearn.preprocessing import StandardScaler, OneHotEncoder\n",
+    "from sklearn.compose import ColumnTransformer\n",
+    "from sklearn.pipeline import Pipeline\n",
+    "from sklearn.linear_model import LinearRegression\n",
+    "from sklearn.tree import DecisionTreeRegressor\n",
+    "from sklearn.ensemble import GradientBoostingRegressor\n",
+    "\n",
+    "df['Date'] = pd.to_datetime(df['Date'], errors='coerce')\n",
+    "\n",
+    "# Извлечение признаков из даты\n",
+    "df['Year'] = df['Date'].dt.year\n",
+    "df['Month'] = df['Date'].dt.month\n",
+    "df['Day'] = df['Date'].dt.day\n",
+    "\n",
+    "categorical_features = [] \n",
+    "numeric_features = ['Year', 'Month', 'Day', 'Open', 'High', 'Low', 'Adj Close', 'Volume']\n",
+    "\n",
+    "target = 'Close'\n",
+    "features = numeric_features + categorical_features\n",
+    "\n",
+    "X_train, X_test, y_train, y_test = train_test_split(df[features], df[target], test_size=0.2, random_state=42)\n",
+    "\n",
+    "preprocessor = ColumnTransformer(\n",
+    "    transformers=[\n",
+    "        ('num', StandardScaler(), numeric_features),\n",
+    "        ('cat', OneHotEncoder(), categorical_features)], \n",
+    "    remainder='passthrough')\n",
+    "\n",
+    "pipeline_linear_regression = Pipeline(steps=[\n",
+    "    ('preprocessor', preprocessor),\n",
+    "    ('regressor', LinearRegression())\n",
+    "])\n",
+    "\n",
+    "pipeline_decision_tree = Pipeline(steps=[\n",
+    "    ('preprocessor', preprocessor),\n",
+    "    ('regressor', DecisionTreeRegressor(random_state=42))\n",
+    "])\n",
+    "\n",
+    "pipeline_gradient_boosting = Pipeline(steps=[\n",
+    "    ('preprocessor', preprocessor),\n",
+    "    ('regressor', GradientBoostingRegressor(random_state=42))\n",
+    "])\n",
+    "\n",
+    "pipelines = [\n",
+    "    ('Linear Regression', pipeline_linear_regression),\n",
+    "    ('Decision Tree', pipeline_decision_tree),\n",
+    "    ('Gradient Boosting', pipeline_gradient_boosting)\n",
+    "]\n",
+    "\n",
+    "for name, pipeline in pipelines:\n",
+    "    pipeline.fit(X_train, y_train)\n",
+    "    print(f\"Model: {name} trained.\")\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### **Оценка качества моделей для регрессии**\n",
+    "\n",
+    "Оценим качество моделей для решения задач регресси и обоснуем выбор метрик."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Model: Linear Regression\n",
+      "MAE: 0.09839901002366848\n",
+      "MSE: 0.021197782995962776\n",
+      "R²: 0.9998363007754062\n",
+      "\n",
+      "Model: Decision Tree\n",
+      "MAE: 0.12540266748366016\n",
+      "MSE: 0.03189181356212172\n",
+      "R²: 0.9997537164545931\n",
+      "\n",
+      "Model: Gradient Boosting\n",
+      "MAE: 0.1251011338066786\n",
+      "MSE: 0.031244571650786104\n",
+      "R²: 0.9997587147602665\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "from sklearn.metrics import mean_absolute_error, mean_squared_error, r2_score\n",
+    "\n",
+    "for name, pipeline in pipelines:\n",
+    "    y_pred = pipeline.predict(X_test)\n",
+    "    print(f\"Model: {name}\")\n",
+    "    print('MAE:', mean_absolute_error(y_test, y_pred))\n",
+    "    print('MSE:', mean_squared_error(y_test, y_pred))\n",
+    "    print('R²:', r2_score(y_test, y_pred))\n",
+    "    print()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**В качестве метрик для оценки качества регрессионных моделей выбраны:**\n",
+    "\n",
+    "- **MAE (Mean Absolute Error)** — средняя абсолютная ошибка. Она измеряет среднюю величину отклонений предсказанных значений от фактических, что позволяет понять, насколько в среднем модель ошибается. MAE удобна для интерпретации, так как измеряется в тех же единицах, что и целевая переменная.\n",
+    "\n",
+    "- **MSE (Mean Squared Error)** — среднеквадратичная ошибка, которая учитывает квадраты ошибок, что увеличивает вес больших ошибок по сравнению с MAE. Это полезно, когда нам нужно сильнее штрафовать крупные отклонения.\n",
+    "\n",
+    "- **R² (коэффициент детерминации)** — доля объясненной дисперсии, которая показывает, насколько хорошо модель объясняет изменчивость целевой переменной. Значение R² близкое к 1 указывает на высокую точность модели, а отрицательные значения — на низкое качество, когда модель хуже, чем простое усреднение.\n",
+    "\n",
+    "\n",
+    "**Анализ результатов:**\n",
+    "1. **Baseline MAE, MSE, R²:**\n",
+    "\n",
+    "- Baseline MAE: 9.22\n",
+    "\n",
+    "- Baseline MSE: 129.81\n",
+    "\n",
+    "- Baseline R²: -0.002\n",
+    "\n",
+    "2. **Linear Regression:**\n",
+    "\n",
+    "- MAE: 0.098\n",
+    "\n",
+    "- MSE: 0.021\n",
+    "\n",
+    "- R²: 0.999\n",
+    "\n",
+    "*Вывод*: Линейная регрессия показала самую низкую ошибку (MAE и MSE) и наивысший R², что указывает на то, что она лучше всего подходит для данного набора данных\n",
+    "\n",
+    "3. **Decision Tree:**\n",
+    "\n",
+    "- MAE: 0.125\n",
+    "\n",
+    "- MSE: 0.031\n",
+    "\n",
+    "- R²: 0.999\n",
+    "\n",
+    "*Вывод*:  Дерево решений показало хорошие результаты, хотя и немного хуже, чем линейная регрессия. R² также очень высокий, что указывает на хорошее объяснение изменчивости данных.\n",
+    "\n",
+    "4. **Gradient Boosting:**\n",
+    "\n",
+    "- MAE: 0.125\n",
+    "\n",
+    "- MSE: 0.031\n",
+    "\n",
+    "- R²: 0.999\n",
+    "\n",
+    "*Вывод*: Градиентный бустинг показал результаты, близкие к дереву решений, но немного лучше по MAE и MSE. R² также очень высокий."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### **Разбиение на выборки и создание ориентира для задач классификации**\n",
+    "\n",
+    "Мы будем использовать подход к задаче регрессии, где целевой переменной будет выступать цена закрытия акции, а другие характеристики выбраны в качестве признаков."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Размер обучающей выборки: (4894, 4)\n",
+      "Размер тестовой выборки: (1224, 4)\n"
+     ]
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "from sklearn.model_selection import train_test_split\n",
+    "\n",
+    "df = pd.read_csv(\"..//static//csv//WMT.csv\")\n",
+    "# Создание целевой переменной для классификации направления изменения цены\n",
+    "# Если цена закрытия следующего дня выше текущего дня — 1 (повышение), иначе — 0 (снижение)\n",
+    "df['Price_Up'] = (df['Close'].shift(-1) > df['Close']).astype(int)\n",
+    "\n",
+    "features = ['Open', 'High', 'Low', 'Volume'] \n",
+    "target = 'Price_Up'\n",
+    "\n",
+    "# Удаление последней строки, так как для неё нет значения следующего дня\n",
+    "df = df.dropna()\n",
+    "\n",
+    "X_train, X_test, y_train, y_test = train_test_split(df[features], df[target], test_size=0.2, random_state=42)\n",
+    "\n",
+    "print(\"Размер обучающей выборки:\", X_train.shape)\n",
+    "print(\"Размер тестовой выборки:\", X_test.shape)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### **Построение конвейера и обучение моделей для задач классификации**\n",
+    "\n",
+    "Построим конвейер где проведем обучение моделей, а так же создадим отдельную переменную 'Price_Up' для точного подсчета направления изменения цены (повышение или понижение) на следующий день."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Accuracy: 0.4880\n",
+      "Precision: 0.4821\n",
+      "Recall: 0.3891\n",
+      "F1-Score: 0.4306\n",
+      "ROC-AUC: 0.4836\n",
+      "Accuracy: 0.4936\n",
+      "Precision: 0.4906\n",
+      "Recall: 0.4630\n",
+      "F1-Score: 0.4764\n",
+      "ROC-AUC: 0.5052\n",
+      "Accuracy: 0.4952\n",
+      "Precision: 0.4923\n",
+      "Recall: 0.4630\n",
+      "F1-Score: 0.4772\n",
+      "ROC-AUC: 0.4972\n",
+      "\n",
+      "Результаты моделей:\n",
+      "\n",
+      "Logistic Regression:\n",
+      "Accuracy: 0.4880\n",
+      "Precision: 0.4821\n",
+      "Recall: 0.3891\n",
+      "F1: 0.4306\n",
+      "Roc_auc: 0.4836\n",
+      "\n",
+      "Random Forest:\n",
+      "Accuracy: 0.4936\n",
+      "Precision: 0.4906\n",
+      "Recall: 0.4630\n",
+      "F1: 0.4764\n",
+      "Roc_auc: 0.5052\n",
+      "\n",
+      "XGBoost:\n",
+      "Accuracy: 0.4952\n",
+      "Precision: 0.4923\n",
+      "Recall: 0.4630\n",
+      "F1: 0.4772\n",
+      "Roc_auc: 0.4972\n"
+     ]
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "from imblearn.over_sampling import SMOTE\n",
+    "from sklearn.model_selection import train_test_split, RandomizedSearchCV\n",
+    "from sklearn.pipeline import Pipeline\n",
+    "from sklearn.preprocessing import StandardScaler\n",
+    "from sklearn.linear_model import LogisticRegression\n",
+    "from sklearn.ensemble import RandomForestClassifier\n",
+    "from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score, roc_auc_score\n",
+    "from scipy.stats import uniform, randint\n",
+    "import xgboost as xgb\n",
+    "\n",
+    "features = ['Open', 'High', 'Low', 'Volume']\n",
+    "target = 'Price_Up'\n",
+    "\n",
+    "X = df[features]\n",
+    "y = df[target]\n",
+    "\n",
+    "smote = SMOTE(random_state=42)\n",
+    "X_resampled, y_resampled = smote.fit_resample(X, y)\n",
+    "\n",
+    "X_train, X_test, y_train, y_test = train_test_split(X_resampled, y_resampled, test_size=0.2, random_state=42)\n",
+    "\n",
+    "def evaluate_model(model, X_test, y_test):\n",
+    "    y_pred = model.predict(X_test)\n",
+    "    y_pred_proba = model.predict_proba(X_test)[:, 1]\n",
+    "    \n",
+    "    accuracy = accuracy_score(y_test, y_pred)\n",
+    "    precision = precision_score(y_test, y_pred)\n",
+    "    recall = recall_score(y_test, y_pred)\n",
+    "    f1 = f1_score(y_test, y_pred)\n",
+    "    roc_auc = roc_auc_score(y_test, y_pred_proba)\n",
+    "    \n",
+    "    print(f\"Accuracy: {accuracy:.4f}\")\n",
+    "    print(f\"Precision: {precision:.4f}\")\n",
+    "    print(f\"Recall: {recall:.4f}\")\n",
+    "    print(f\"F1-Score: {f1:.4f}\")\n",
+    "    print(f\"ROC-AUC: {roc_auc:.4f}\")\n",
+    "    \n",
+    "    return {'accuracy': accuracy, 'precision': precision, 'recall': recall, 'f1': f1, 'roc_auc': roc_auc}\n",
+    "\n",
+    "\n",
+    "# Логистическая регрессия\n",
+    "logreg_pipeline = Pipeline([\n",
+    "    ('scaler', StandardScaler()),\n",
+    "    ('classifier', LogisticRegression(max_iter=1000, random_state=42))\n",
+    "])\n",
+    "logreg_param_dist = {\n",
+    "    'classifier__C': uniform(loc=0, scale=4),\n",
+    "    'classifier__penalty': ['l1', 'l2'],\n",
+    "    'classifier__solver': ['liblinear', 'saga']\n",
+    "}\n",
+    "logreg_random_search = RandomizedSearchCV(logreg_pipeline, param_distributions=logreg_param_dist, n_iter=50, cv=5, random_state=42, n_jobs=-1)\n",
+    "logreg_random_search.fit(X_train, y_train)\n",
+    "logreg_best_model = logreg_random_search.best_estimator_\n",
+    "logreg_results = evaluate_model(logreg_best_model, X_test, y_test)\n",
+    "\n",
+    "# Случайный лес\n",
+    "rf_pipeline = Pipeline([\n",
+    "    ('scaler', StandardScaler()),\n",
+    "    ('classifier', RandomForestClassifier(random_state=42))\n",
+    "])\n",
+    "rf_param_dist = {\n",
+    "    'classifier__n_estimators': randint(100, 1000),\n",
+    "    'classifier__max_depth': [None] + list(randint(10, 100).rvs(10)),\n",
+    "    'classifier__min_samples_split': randint(2, 20),\n",
+    "    'classifier__min_samples_leaf': randint(1, 20),\n",
+    "    'classifier__bootstrap': [True, False]\n",
+    "}\n",
+    "rf_random_search = RandomizedSearchCV(rf_pipeline, param_distributions=rf_param_dist, n_iter=50, cv=5, random_state=42, n_jobs=-1)\n",
+    "rf_random_search.fit(X_train, y_train)\n",
+    "rf_best_model = rf_random_search.best_estimator_\n",
+    "rf_results = evaluate_model(rf_best_model, X_test, y_test)\n",
+    "\n",
+    "# XGBoost\n",
+    "xgb_pipeline = Pipeline([\n",
+    "    ('scaler', StandardScaler()),\n",
+    "    ('classifier', xgb.XGBClassifier(random_state=42))\n",
+    "])\n",
+    "xgb_param_dist = {\n",
+    "    'classifier__n_estimators': randint(100, 1000),\n",
+    "    'classifier__learning_rate': uniform(0.01, 0.5),\n",
+    "    'classifier__max_depth': randint(3, 10),\n",
+    "    'classifier__min_child_weight': randint(1, 10),\n",
+    "    'classifier__subsample': uniform(0.5, 0.5),\n",
+    "    'classifier__colsample_bytree': uniform(0.5, 0.5)\n",
+    "}\n",
+    "xgb_random_search = RandomizedSearchCV(xgb_pipeline, param_distributions=xgb_param_dist, n_iter=50, cv=5, random_state=42, n_jobs=-1)\n",
+    "xgb_random_search.fit(X_train, y_train)\n",
+    "xgb_best_model = xgb_random_search.best_estimator_\n",
+    "xgb_results = evaluate_model(xgb_best_model, X_test, y_test)\n",
+    "\n",
+    "print(\"\\nРезультаты моделей:\")\n",
+    "print(\"\\nLogistic Regression:\")\n",
+    "for metric, value in logreg_results.items():\n",
+    "    print(f\"{metric.capitalize()}: {value:.4f}\")\n",
+    "\n",
+    "print(\"\\nRandom Forest:\")\n",
+    "for metric, value in rf_results.items():\n",
+    "    print(f\"{metric.capitalize()}: {value:.4f}\")\n",
+    "\n",
+    "print(\"\\nXGBoost:\")\n",
+    "for metric, value in xgb_results.items():\n",
+    "    print(f\"{metric.capitalize()}: {value:.4f}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### **Оценка качества моделей для классификации**\n",
+    "\n",
+    "Оценим качество моделей для решения задач классификации и обоснуем выбор метрик. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Logistic Regression Metrics:\n",
+      "Accuracy: 0.4880\n",
+      "Precision: 0.4821\n",
+      "Recall: 0.3891\n",
+      "F1-Score: 0.4306\n",
+      "ROC-AUC: 0.4836\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 600x500 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 800x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Random Forest Metrics:\n",
+      "Accuracy: 0.4936\n",
+      "Precision: 0.4906\n",
+      "Recall: 0.4630\n",
+      "F1-Score: 0.4764\n",
+      "ROC-AUC: 0.5052\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 600x500 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 800x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Gradient Boosting Metrics:\n",
+      "Accuracy: 0.4952\n",
+      "Precision: 0.4923\n",
+      "Recall: 0.4630\n",
+      "F1-Score: 0.4772\n",
+      "ROC-AUC: 0.4972\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 600x500 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 800x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import seaborn as sns\n",
+    "import matplotlib.pyplot as plt\n",
+    "from sklearn.metrics import confusion_matrix, roc_curve, auc, accuracy_score, precision_score, recall_score, f1_score, roc_auc_score\n",
+    "\n",
+    "sns.set(style=\"whitegrid\")\n",
+    "\n",
+    "def plot_confusion_matrix(y_true, y_pred, title):\n",
+    "    cm = confusion_matrix(y_true, y_pred)\n",
+    "    plt.figure(figsize=(6, 5))\n",
+    "    ax = sns.heatmap(cm, annot=True, fmt='d', cmap='coolwarm', cbar=True, annot_kws={\"size\": 14})\n",
+    "    plt.title(title, fontsize=16)\n",
+    "    plt.xlabel('Предсказанные значения', fontsize=12)\n",
+    "    plt.ylabel('Истинные значения', fontsize=12)\n",
+    "    plt.xticks(fontsize=10)\n",
+    "    plt.yticks(fontsize=10)\n",
+    "    cbar = ax.collections[0].colorbar\n",
+    "    cbar.set_label('Count', rotation=270, labelpad=20, fontsize=12)\n",
+    "    plt.show() \n",
+    "\n",
+    "def plot_roc_curve(y_true, y_pred_proba, title):\n",
+    "    fpr, tpr, _ = roc_curve(y_true, y_pred_proba)\n",
+    "    roc_auc = auc(fpr, tpr)\n",
+    "    \n",
+    "    plt.figure(figsize=(8, 6))\n",
+    "    plt.plot(fpr, tpr, color='#FF6347', lw=2, label=f'ROC curve (AUC = {roc_auc:.2f})')\n",
+    "    plt.plot([0, 1], [0, 1], color='gray', linestyle='--', lw=1.5, label='Random Guess')\n",
+    "    plt.xlim([0.0, 1.0])\n",
+    "    plt.ylim([0.0, 1.05])\n",
+    "    plt.xlabel('Показатель ложных положительных результатов', fontsize=12)\n",
+    "    plt.ylabel('Показатель истинных положительных результатов', fontsize=12)\n",
+    "    plt.title(title, fontsize=16)\n",
+    "    plt.legend(loc=\"lower right\", fontsize=10)\n",
+    "    plt.grid(True, linestyle='--', alpha=0.6)\n",
+    "    plt.show()\n",
+    "\n",
+    "def evaluate_and_plot_model(model, X_test, y_test, model_name):\n",
+    "    y_pred = model.predict(X_test)\n",
+    "    y_pred_proba = model.predict_proba(X_test)[:, 1]\n",
+    "    \n",
+    "    accuracy = accuracy_score(y_test, y_pred)\n",
+    "    precision = precision_score(y_test, y_pred, pos_label=1)\n",
+    "    recall = recall_score(y_test, y_pred, pos_label=1)\n",
+    "    f1 = f1_score(y_test, y_pred, pos_label=1)\n",
+    "    roc_auc = roc_auc_score(y_test, y_pred_proba)\n",
+    "    \n",
+    "    print(f\"\\n{model_name} Metrics:\")\n",
+    "    print(f\"Accuracy: {accuracy:.4f}\")\n",
+    "    print(f\"Precision: {precision:.4f}\")\n",
+    "    print(f\"Recall: {recall:.4f}\")\n",
+    "    print(f\"F1-Score: {f1:.4f}\")\n",
+    "    print(f\"ROC-AUC: {roc_auc:.4f}\")\n",
+    "    \n",
+    "    plot_confusion_matrix(y_test, y_pred, f'Confusion Matrix for {model_name}')\n",
+    "    plot_roc_curve(y_test, y_pred_proba, f'ROC Curve for {model_name}')\n",
+    "\n",
+    "evaluate_and_plot_model(logreg_best_model, X_test, y_test, 'Logistic Regression')\n",
+    "evaluate_and_plot_model(rf_best_model, X_test, y_test, 'Random Forest')\n",
+    "evaluate_and_plot_model(xgb_best_model, X_test, y_test, 'Gradient Boosting')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Вывод по результатам задач классификации**  \n",
+    "Результаты обучения моделей для задачи классификации направления изменения цены показали, что качество прогнозирования остаётся на уровне случайного угадывания.\n",
+    "\n",
+    "**Анализ метрик для моделей:**\n",
+    "\n",
+    "- **Логистическая регрессия:** Данная модель показала точность (Accuracy) 0.4880 и F1-меру 0.4306. Значения Precision (0.4821) и Recall (0.3891) также указывают на трудности модели с корректной классификацией. ROC-AUC на уровне 0.4836 близок к случайному значению (0.5), что говорит о слабой предсказательной способности.\n",
+    "\n",
+    "- **Случайный лес:** Случайный лес продемонстрировал лучшие результаты по сравнению с логистической регрессией: точность 0.4936 и F1-меру 0.4764. Метрика ROC-AUC составила 0.5052, что превышает уровень случайного угадывания, но не является достаточным показателем качества.\n",
+    "\n",
+    "- **Градиентный бустинг:** Градиентный бустинг показал схожие результаты со случайным лесом: точность 0.4952, F1-меру 0.4772, и ROC-AUC на уровне 0.4972. Данные значения говорят о том, что, несмотря на сложности задачи, эта модель на данный момент является наилучшей из предложенных."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "miienv",
+   "language": "python",
+   "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": "3.12.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/lab_4/requirements b/lab_4/requirements
new file mode 100644
index 0000000..3e3dd51
Binary files /dev/null and b/lab_4/requirements differ