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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Лабораторная работа №3\n",
+    "\n",
+    "## Набор данных Students Performance in Exams (Успеваемость студентов на экзаменах)\n",
+    "\n",
+    "Выгрузка данных из CSV файла в датафрейм"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 315,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Index(['gender', 'race/ethnicity', 'parental level of education', 'lunch',\n",
+      "       'test preparation course', 'math score', 'reading score',\n",
+      "       'writing score'],\n",
+      "      dtype='object')\n",
+      "\n",
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "RangeIndex: 1000 entries, 0 to 999\n",
+      "Data columns (total 8 columns):\n",
+      " #   Column                       Non-Null Count  Dtype \n",
+      "---  ------                       --------------  ----- \n",
+      " 0   gender                       1000 non-null   object\n",
+      " 1   race/ethnicity               1000 non-null   object\n",
+      " 2   parental level of education  1000 non-null   object\n",
+      " 3   lunch                        1000 non-null   object\n",
+      " 4   test preparation course      1000 non-null   object\n",
+      " 5   math score                   1000 non-null   int64 \n",
+      " 6   reading score                1000 non-null   int64 \n",
+      " 7   writing score                1000 non-null   int64 \n",
+      "dtypes: int64(3), object(5)\n",
+      "memory usage: 62.6+ KB\n"
+     ]
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns\n",
+    "import numpy as np\n",
+    "\n",
+    "# Загрузка данных\n",
+    "df = pd.read_csv(\"..//..//static//csv//StudentsPerformance.csv\")\n",
+    "\n",
+    "# Вывод колонок\n",
+    "print(df.columns)\n",
+    "\n",
+    "print()\n",
+    "\n",
+    "df.info()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Описание набора  \n",
+    "\n",
+    "Контекст\n",
+    "Оценки, полученные студентами\n",
+    "\n",
+    "Содержание\n",
+    "Этот набор данных состоит из оценок, полученных учащимися по различным предметам.\n",
+    "\n",
+    "Вдохновение\n",
+    "Понять влияние происхождения родителей, подготовки к тестированию и т. д. на успеваемость учащихся."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 316,
+   "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>gender</th>\n",
+       "      <th>race/ethnicity</th>\n",
+       "      <th>parental level of education</th>\n",
+       "      <th>lunch</th>\n",
+       "      <th>test preparation course</th>\n",
+       "      <th>math score</th>\n",
+       "      <th>reading score</th>\n",
+       "      <th>writing score</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>female</td>\n",
+       "      <td>group B</td>\n",
+       "      <td>bachelor's degree</td>\n",
+       "      <td>standard</td>\n",
+       "      <td>none</td>\n",
+       "      <td>72</td>\n",
+       "      <td>72</td>\n",
+       "      <td>74</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>female</td>\n",
+       "      <td>group C</td>\n",
+       "      <td>some college</td>\n",
+       "      <td>standard</td>\n",
+       "      <td>completed</td>\n",
+       "      <td>69</td>\n",
+       "      <td>90</td>\n",
+       "      <td>88</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>female</td>\n",
+       "      <td>group B</td>\n",
+       "      <td>master's degree</td>\n",
+       "      <td>standard</td>\n",
+       "      <td>none</td>\n",
+       "      <td>90</td>\n",
+       "      <td>95</td>\n",
+       "      <td>93</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>male</td>\n",
+       "      <td>group A</td>\n",
+       "      <td>associate's degree</td>\n",
+       "      <td>free/reduced</td>\n",
+       "      <td>none</td>\n",
+       "      <td>47</td>\n",
+       "      <td>57</td>\n",
+       "      <td>44</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>male</td>\n",
+       "      <td>group C</td>\n",
+       "      <td>some college</td>\n",
+       "      <td>standard</td>\n",
+       "      <td>none</td>\n",
+       "      <td>76</td>\n",
+       "      <td>78</td>\n",
+       "      <td>75</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   gender race/ethnicity parental level of education         lunch  \\\n",
+       "0  female        group B           bachelor's degree      standard   \n",
+       "1  female        group C                some college      standard   \n",
+       "2  female        group B             master's degree      standard   \n",
+       "3    male        group A          associate's degree  free/reduced   \n",
+       "4    male        group C                some college      standard   \n",
+       "\n",
+       "  test preparation course  math score  reading score  writing score  \n",
+       "0                    none          72             72             74  \n",
+       "1               completed          69             90             88  \n",
+       "2                    none          90             95             93  \n",
+       "3                    none          47             57             44  \n",
+       "4                    none          76             78             75  "
+      ]
+     },
+     "execution_count": 316,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Вывод столбцов\n",
+    "df.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 317,
+   "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>math score</th>\n",
+       "      <th>reading score</th>\n",
+       "      <th>writing score</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>count</th>\n",
+       "      <td>1000.00000</td>\n",
+       "      <td>1000.000000</td>\n",
+       "      <td>1000.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>mean</th>\n",
+       "      <td>66.08900</td>\n",
+       "      <td>69.169000</td>\n",
+       "      <td>68.054000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>std</th>\n",
+       "      <td>15.16308</td>\n",
+       "      <td>14.600192</td>\n",
+       "      <td>15.195657</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>min</th>\n",
+       "      <td>0.00000</td>\n",
+       "      <td>17.000000</td>\n",
+       "      <td>10.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25%</th>\n",
+       "      <td>57.00000</td>\n",
+       "      <td>59.000000</td>\n",
+       "      <td>57.750000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50%</th>\n",
+       "      <td>66.00000</td>\n",
+       "      <td>70.000000</td>\n",
+       "      <td>69.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>75%</th>\n",
+       "      <td>77.00000</td>\n",
+       "      <td>79.000000</td>\n",
+       "      <td>79.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>max</th>\n",
+       "      <td>100.00000</td>\n",
+       "      <td>100.000000</td>\n",
+       "      <td>100.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       math score  reading score  writing score\n",
+       "count  1000.00000    1000.000000    1000.000000\n",
+       "mean     66.08900      69.169000      68.054000\n",
+       "std      15.16308      14.600192      15.195657\n",
+       "min       0.00000      17.000000      10.000000\n",
+       "25%      57.00000      59.000000      57.750000\n",
+       "50%      66.00000      70.000000      69.000000\n",
+       "75%      77.00000      79.000000      79.000000\n",
+       "max     100.00000     100.000000     100.000000"
+      ]
+     },
+     "execution_count": 317,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Краткая статистическая сводка для данных:\n",
+    "df.describe()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Анализ содержимого\n",
+    "\n",
+    "*Объекты наблюдения:* студенты, участвующие в экзаменах.\n",
+    "\n",
+    "*Атрибуты объектов:* \n",
+    "\n",
+    "1. gender — пол: определяет гендерную принадлежность студента (мужской, женский).  \n",
+    "2. race/ethnicity — этническая принадлежность: группа, к которой относится студент (например, различные расовые/этнические категории).  \n",
+    "3. parental level of education — уровень образования родителей(например, среднее образование, высшее образование и т.д.).  \n",
+    "4. lunch — тип обеда: информация о том, получает ли студент бесплатный или платный обед.  \n",
+    "5. test preparation course — курс подготовки к тесту\n",
+    "6. math score  — результаты экзаменов по математике.\n",
+    "7. reading score — результаты экзаменов по чтению.\n",
+    "8. writing score — результаты экзаменов по письму.\n",
+    "\n",
+    "\n",
+    "### Бизнес-цель\n",
+    "1.  Анализ факторов, влияющих на успеваемость студентов:\n",
+    "\n",
+    "    **Цель:** Исследовать, как различные факторы, такие как пол, этническая принадлежность, уровень образования родителей, тип обеда и наличие курса подготовки к тесту, влияют на оценки студентов по математике, чтению и письму.\n",
+    "\n",
+    "    **Эффект:** Это поможет образовательным учреждениям и политикам лучше понять, какие аспекты могут быть улучшены для повышения успеваемости студентов, а также выявить возможные неравенства в образовательных возможностях.\n",
+    "\n",
+    "2.  Прогнозирование успеваемости студентов\n",
+    "\n",
+    "    **Цель:** Разработать модель прогнозирования успеваемости студентов на основе имеющихся данных, таких как пол, раса/этническая принадлежность, уровень образования родителей, тип обеда и участие в подготовительных курсах.\n",
+    "\n",
+    "    **Эффект:** Это позволит предсказать, какие студенты могут столкнуться с трудностями в обучении, и принять меры для их поддержки. Например, образовательные учреждения могут инициировать дополнительные занятия или индивидуальные консультации для студентов, у которых ожидаются низкие результаты на экзаменах, тем самым повышая их шансы на успешную сдачу экзаменов.\n",
+    "\n",
+    "### Техническая цель\n",
+    "1.  Разработка системы анализа факторов успеваемости студентов:\n",
+    "\n",
+    "    **Цель:** Создать аналитическую платформу, которая будет собирать, обрабатывать и визуализировать данные о студентах, включая их оценки и соответствующие факторы (пол, этническая принадлежность, уровень образования родителей, тип обеда, наличие подготовительных курсов).\n",
+    "\n",
+    "2.  Создание модели прогнозирования успеваемости студентов:\n",
+    "\n",
+    "    **Цель:** Разработать и внедрить предсказательную модель, которая будет оценивать вероятную успеваемость студентов на основании их характеристик и данных.\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Анализ данных "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 318,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "gender                         0\n",
+       "race/ethnicity                 0\n",
+       "parental level of education    0\n",
+       "lunch                          0\n",
+       "test preparation course        0\n",
+       "math score                     0\n",
+       "reading score                  0\n",
+       "writing score                  0\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 318,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Проверка на пропущенные данные\n",
+    "df.isnull().sum()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Нет пропущенных данных"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 319,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x1000 with 8 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Построим графики boxplot для обнаружения выбросов по каждой характеристике\n",
+    "plt.figure(figsize=(10, 10))\n",
+    "\n",
+    "# Создание boxplot\n",
+    "for i, column in enumerate(['gender', 'race/ethnicity','parental level of education','lunch','test preparation course','math score','reading score','writing score'], 1):\n",
+    "    plt.subplot(8, 3, i)\n",
+    "    sns.boxplot(x=df[column])\n",
+    "    plt.title(f\"Boxplot для {column}\")\n",
+    "    \n",
+    "plt.tight_layout()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Для автоматического анализа выбросов мы можем использовать несколько методов, которые помогут оценить, являются ли данные выбросами и какие из них стоит оставить или удалить. Давайте используем следующие подходы:\n",
+    "\n",
+    "Метод межквартильного размаха (IQR) — это один из самых популярных способов для обнаружения выбросов. Мы будем искать значения, которые выходят за пределы \n",
+    "1.5×IQR, где IQR — это разница между 75-м и 25-м процентилем данных.\n",
+    "\n",
+    "Z-оценка — этот метод позволяет определить, насколько отклоняется значение от среднего в терминах стандартного отклонения. Обычно выбросами считаются значения, для которых Z-оценка больше 3 или меньше -3."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 320,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Выбросы по методу IQR:\n",
+      "math score: 8 выбросов\n",
+      "reading score: 6 выбросов\n",
+      "writing score: 5 выбросов\n",
+      "\n",
+      "Выбросы по методу Z-оценки:\n",
+      "math score: 4 выбросов\n",
+      "reading score: 4 выбросов\n",
+      "writing score: 4 выбросов\n"
+     ]
+    }
+   ],
+   "source": [
+    "import numpy as np\n",
+    "\n",
+    "# Функция для поиска выбросов по методу IQR\n",
+    "def find_outliers_iqr(df, columns):\n",
+    "    outliers = {}\n",
+    "    for column in columns:\n",
+    "        Q1 = df[column].quantile(0.25)\n",
+    "        Q3 = df[column].quantile(0.75)\n",
+    "        IQR = Q3 - Q1\n",
+    "        lower_bound = Q1 - 1.5 * IQR\n",
+    "        upper_bound = Q3 + 1.5 * IQR\n",
+    "        outliers[column] = df[(df[column] < lower_bound) | (df[column] > upper_bound)]\n",
+    "    return outliers\n",
+    "\n",
+    "# Функция для поиска выбросов по методу Z-оценки\n",
+    "def find_outliers_z(df, columns, threshold=3):\n",
+    "    outliers = {}\n",
+    "    for column in columns:\n",
+    "        z_scores = (df[column] - df[column].mean()) / df[column].std()\n",
+    "        outliers[column] = df[np.abs(z_scores) > threshold]\n",
+    "    return outliers\n",
+    "\n",
+    "# Вычисление выбросов для математических, чтения и письма\n",
+    "columns_to_check = ['math score', 'reading score', 'writing score']\n",
+    "outliers_iqr = find_outliers_iqr(df, columns_to_check)\n",
+    "outliers_z = find_outliers_z(df, columns_to_check)\n",
+    "\n",
+    "# Выводим результаты\n",
+    "print(\"Выбросы по методу IQR:\")\n",
+    "for col, data in outliers_iqr.items():\n",
+    "    print(f\"{col}: {data.shape[0]} выбросов\")\n",
+    "\n",
+    "print(\"\\nВыбросы по методу Z-оценки:\")\n",
+    "for col, data in outliers_z.items():\n",
+    "    print(f\"{col}: {data.shape[0]} выбросов\")\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Так как выбросы по Z-оценке и IQR частично совпадают, это подтверждает их значимость в данных.\n",
+    "\n",
+    "Попробуем решить устранить проблему выбросов для writing score и reading score и math score, заменив их на медиану. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 321,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x500 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Функция для замены выбросов на медиану\n",
+    "def replace_outliers_with_median(df, columns):\n",
+    "    for column in columns:\n",
+    "        # Находим границы по методу IQR\n",
+    "        Q1 = df[column].quantile(0.25)\n",
+    "        Q3 = df[column].quantile(0.75)\n",
+    "        IQR = Q3 - Q1\n",
+    "        lower_bound = Q1 - 1.5 * IQR\n",
+    "        upper_bound = Q3 + 1.5 * IQR\n",
+    "        \n",
+    "        # Заменяем выбросы на медиану\n",
+    "        median = df[column].median()\n",
+    "        df[column] = df[column].apply(lambda x: median if x < lower_bound or x > upper_bound else x)\n",
+    "    \n",
+    "    return df\n",
+    "\n",
+    "# Заменим выбросы на медиану для баллов\n",
+    "df = replace_outliers_with_median(df.copy(), columns_to_check)\n",
+    "\n",
+    "\n",
+    "# Построим графики для проверки\n",
+    "plt.figure(figsize=(10, 5))\n",
+    "\n",
+    "# Создание boxplot\n",
+    "for i, column in enumerate(['math score','reading score','writing score'], 1):\n",
+    "    plt.subplot(3, 3, i)\n",
+    "    sns.boxplot(x=df[column])\n",
+    "    plt.title(f\"Boxplot для {column}\")\n",
+    "    \n",
+    "plt.tight_layout()\n",
+    "plt.show()\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Связи между объектами:\n",
+    "\n",
+    " Анализ данных покажет, как каждый из атрибутов (пол, этническая принадлежность, уровень образования родителей, тип обеда, курс подготовки) влияет на оценки студентов, что поможет выявить ключевые факторы, способствующие или препятствующие успеваемости."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 322,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x600 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Расчет корреляции между оценками по математике, чтению и письму\n",
+    "correlation_matrix = df[['math score', 'reading score', 'writing score']].corr()\n",
+    "\n",
+    "# Визуализация матрицы корреляций\n",
+    "import seaborn as sns\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "plt.figure(figsize=(8, 6))\n",
+    "sns.heatmap(correlation_matrix, annot=True, cmap='coolwarm', fmt='.2f', linewidths=0.5)\n",
+    "plt.title('Корреляция между оценками по математике, чтению и письму')\n",
+    "plt.show()\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Корреляция между всеми тремя оценками высока, особенно между оценками по чтению и письму (0.95), а также между чтением и математикой (0.78). Это говорит о том, что студенты, которые показывают высокие результаты в одном из этих предметов, обычно показывают хорошие результаты и в других предметах.\n",
+    "\n",
+    "Математика имеет наиболее слабую корреляцию с другими предметами (0.78 и 0.76), но все равно достаточно значимую. Это может означать, что успехи в математике несколько менее связаны с успехами в чтении и письме, чем между чтением и письмом, но все же есть определенная связь.\n",
+    "\n",
+    "Чтение и письмо имеют почти идеальную корреляцию (0.95), что указывает на очень высокую взаимосвязь между этими двумя видами деятельности. Это может свидетельствовать о том, что навыки, необходимые для хорошего выполнения задания по чтению, схожи с теми, что необходимы для успешного написания текста.\n",
+    "\n",
+    "Если целью является улучшение успеваемости студентов, стоит сосредоточиться на факторах, которые могут улучшить все три навыка одновременно. Например, можно обратить внимание на методы, развивающие как читаемость, так и письмо, так как они сильно взаимосвязаны.\n",
+    "Математика может потребовать отдельного внимания или подхода, так как ее корреляция с чтением и письмом ниже, чем между чтением и письмом."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 323,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1200x800 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Влияние пола на оценки\n",
+    "plt.figure(figsize=(12, 8))\n",
+    "\n",
+    "# Boxplot для math score по полу\n",
+    "plt.subplot(2, 2, 1)\n",
+    "sns.boxplot(x='gender', y='math score', data=df)\n",
+    "plt.title('Влияние пола на math score')\n",
+    "\n",
+    "# Boxplot для reading score по полу\n",
+    "plt.subplot(2, 2, 2)\n",
+    "sns.boxplot(x='gender', y='reading score', data=df)\n",
+    "plt.title('Влияние пола на reading score')\n",
+    "\n",
+    "# Boxplot для writing score по полу\n",
+    "plt.subplot(2, 2, 3)\n",
+    "sns.boxplot(x='gender', y='writing score', data=df)\n",
+    "plt.title('Влияние пола на writing score')\n",
+    "\n",
+    "plt.tight_layout()\n",
+    "plt.show()\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Женщины, как правило, демонстрируют лучшие результаты в чтении и письме, чем мужчины, в то время как в математике различие менее выражено.\n",
+    "\n",
+    "Для мужчин характерны выбросы с низкими оценками в чтении и письме, что может свидетельствовать о необходимости дополнительной поддержки или изменений в методиках обучения.\n",
+    "\n",
+    "Женщины могут иметь более высокие и стабильные результаты, что также заслуживает внимания для дальнейших исследований."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 324,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1500x1000 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Влияние этнической принадлежности на оценки\n",
+    "plt.figure(figsize=(15, 10))\n",
+    "\n",
+    "# Boxplot для math score по этнической принадлежности\n",
+    "plt.subplot(3, 2, 1)\n",
+    "sns.boxplot(x='race/ethnicity', y='math score', data=df)\n",
+    "plt.title('Влияние этнической принадлежности на math score')\n",
+    "\n",
+    "# Boxplot для reading score по этнической принадлежности\n",
+    "plt.subplot(3, 2, 2)\n",
+    "sns.boxplot(x='race/ethnicity', y='reading score', data=df)\n",
+    "plt.title('Влияние этнической принадлежности на reading score')\n",
+    "\n",
+    "# Boxplot для writing score по этнической принадлежности\n",
+    "plt.subplot(3, 2, 3)\n",
+    "sns.boxplot(x='race/ethnicity', y='writing score', data=df)\n",
+    "plt.title('Влияние этнической принадлежности на writing score')\n",
+    "\n",
+    "plt.tight_layout()\n",
+    "plt.show()\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Этническая принадлежность имеет значительное влияние на успеваемость студентов, особенно между группами с более высокими и более низкими результатами. Это подтверждается тем, что группы E и D стабильно показывают более высокие результаты, чем другие.\n",
+    "\n",
+    "Этот фактор следует учитывать при разработке методов поддержания успеха студентов, особенно в группах с более низкими результатами."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 325,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1500x1000 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Влияние уровня образования родителей на оценки\n",
+    "plt.figure(figsize=(15, 10))\n",
+    "\n",
+    "# Boxplot для math score по уровню образования родителей\n",
+    "plt.subplot(3, 2, 1)\n",
+    "sns.boxplot(x='parental level of education', y='math score', data=df)\n",
+    "plt.title('Влияние уровня образования родителей на math score')\n",
+    "\n",
+    "# Boxplot для reading score по уровню образования родителей\n",
+    "plt.subplot(3, 2, 2)\n",
+    "sns.boxplot(x='parental level of education', y='reading score', data=df)\n",
+    "plt.title('Влияние уровня образования родителей на reading score')\n",
+    "\n",
+    "# Boxplot для writing score по уровню образования родителей\n",
+    "plt.subplot(3, 2, 3)\n",
+    "sns.boxplot(x='parental level of education', y='writing score', data=df)\n",
+    "plt.title('Влияние уровня образования родителей на writing score')\n",
+    "\n",
+    "plt.tight_layout()\n",
+    "plt.show()\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Уровень образования родителей оказывает значительное влияние на успеваемость студентов по всем предметам: математике, чтению и письму. Студенты с родителями, имеющими высшее образование (особенно степень бакалавра или выше), показывают наивысшие результаты, а также более стабильные оценки.  \n",
+    "\n",
+    "Студенты с родителями, имеющими среднее образование или диплом старшей школы, имеют более низкие результаты и большую вариативность, что может свидетельствовать о разнице в образовательных возможностях, доступных этим студентам.  \n",
+    "\n",
+    "Выбросы в некоторых группах (особенно у студентов с родителями с средним образованием и дипломом старшей школы) могут указывать на случаи, когда студенты из этих категорий столкнулись с дополнительными трудностями в учебе, возможно, из-за менее квалифицированных условий обучения или недостаточной поддержки."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 326,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1200x800 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Влияние курса подготовки на оценки\n",
+    "plt.figure(figsize=(12, 8))\n",
+    "\n",
+    "# Boxplot для math score по курсу подготовки\n",
+    "plt.subplot(2, 2, 1)\n",
+    "sns.boxplot(x='test preparation course', y='math score', data=df)\n",
+    "plt.title('Влияние курса подготовки на math score')\n",
+    "\n",
+    "# Boxplot для reading score по курсу подготовки\n",
+    "plt.subplot(2, 2, 2)\n",
+    "sns.boxplot(x='test preparation course', y='reading score', data=df)\n",
+    "plt.title('Влияние курса подготовки на reading score')\n",
+    "\n",
+    "# Boxplot для writing score по курсу подготовки\n",
+    "plt.subplot(2, 2, 3)\n",
+    "sns.boxplot(x='test preparation course', y='writing score', data=df)\n",
+    "plt.title('Влияние курса подготовки на writing score')\n",
+    "\n",
+    "plt.tight_layout()\n",
+    "plt.show()\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Курс подготовки оказывает положительное влияние на успеваемость студентов во всех трех предметах, особенно по математике и письму.  \n",
+    "\n",
+    "Студенты, прошедшие курс подготовки, имеют значительно более высокие оценки и меньше выбросов с низкими баллами.\n",
+    "\n",
+    "Это подтверждает важность подготовки студентов перед экзаменами, что помогает улучшить их успеваемость и снизить уровень неудач в учебе."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 327,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1200x800 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Влияние курса подготовки на оценки\n",
+    "plt.figure(figsize=(12, 8))\n",
+    "\n",
+    "# Boxplot для math score по курсу подготовки\n",
+    "plt.subplot(2, 2, 1)\n",
+    "sns.boxplot(x='lunch', y='math score', data=df)\n",
+    "plt.title('Влияние типа обеда на math score')\n",
+    "\n",
+    "# Boxplot для reading score по курсу подготовки\n",
+    "plt.subplot(2, 2, 2)\n",
+    "sns.boxplot(x='lunch', y='reading score', data=df)\n",
+    "plt.title('Влияние типа обеда на reading score')\n",
+    "\n",
+    "# Boxplot для writing score по курсу подготовки\n",
+    "plt.subplot(2, 2, 3)\n",
+    "sns.boxplot(x='lunch', y='writing score', data=df)\n",
+    "plt.title('Влияние типа обеда на writing score')\n",
+    "\n",
+    "plt.tight_layout()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Тип обеда действительно может оказывать влияние на успеваемость студентов. Разница в оценках между группами standard и free/reduced указывает на то, что этот признак важен для анализа.\n",
+    "\n",
+    "Студенты с бесплатными обедами в среднем показывают меньше стабильности в результатах, что можно связать с другими социальными и экономическими факторами, влияющими на их учебный процесс."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Исходя из анализа и результатов, мы можем выбрать только те признаки, которые действительно оказывают влияние на успеваемость студентов:\n",
+    "\n",
+    "1. gender (пол) — оказывает влияние на успеваемость, особенно в письме и чтении.  \n",
+    "2. parental level of education (уровень образования родителей) — важный фактор, сильно влияющий на успеваемость.\n",
+    "3. test preparation course (курс подготовки к тесту) — влияет на результаты студентов, особенно по математике и письму.\n",
+    "4. lunch (тип обеда) — имеет влияние, хоть и менее выраженное, но все же важно для предсказания успеваемости.\n",
+    "5. race/ethnicity (этническая принадлежность) — оказывает влияние на успеваемость, особенно в различиях между группами с высокими и низкими результатами.\n",
+    "\n",
+    "Эти признаки имеют заметное влияние на успеваемость студентов, и они будут полезны для построения более точной модели."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Конструирование признаков для решения задач\n",
+    "\n",
+    "1. Новый общий признак — Общий балл  \n",
+    "\n",
+    "    Можно создать новый признак, который будет представлять общую успеваемость студента. Например, можно суммировать баллы по всем предметам и создать общий балл. Это поможет улучшить предсказание на основе общего уровня успеваемости студента.\n",
+    "\n",
+    "    Пример: total_score = math_score + reading_score + writing_score\n",
+    "\n",
+    "\n",
+    "2. Категоризация баллов\n",
+    "\n",
+    "    Использование дискретизации числовых признаков (например, преобразование баллов в категории) может быть полезным для обучения модели, которая будет работать с дискретными данными, а не с непрерывными.\n",
+    "\n",
+    "    Примеры категорий:\n",
+    "\n",
+    "    \"Low\", \"Medium\", \"High\" для баллов\n",
+    "    Классификация на основе квантилей или фиксированных пороговых значений.\n",
+    "\n",
+    "3. Моделирование категориальных признаков\n",
+    "\n",
+    "    Для категориальных признаков (таких как gender, race/ethnicity, parental level of education, lunch, test preparation course) необходимо выполнить one-hot encoding (унитарное кодирование), чтобы модель могла работать с ними.\n",
+    "\n",
+    "4. Масштабирование числовых признаков:  \n",
+    "\n",
+    "    Стандартизируем числовые признаки (например, total_score)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 328,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "   math score  reading score  writing score  gender_male  \\\n",
+      "0        72.0           72.0           74.0        False   \n",
+      "1        69.0           90.0           88.0        False   \n",
+      "2        90.0           95.0           93.0        False   \n",
+      "3        47.0           57.0           44.0         True   \n",
+      "4        76.0           78.0           75.0         True   \n",
+      "\n",
+      "   race/ethnicity_group B  race/ethnicity_group C  race/ethnicity_group D  \\\n",
+      "0                    True                   False                   False   \n",
+      "1                   False                    True                   False   \n",
+      "2                    True                   False                   False   \n",
+      "3                   False                   False                   False   \n",
+      "4                   False                    True                   False   \n",
+      "\n",
+      "   race/ethnicity_group E  parental level of education_bachelor's degree  \\\n",
+      "0                   False                                           True   \n",
+      "1                   False                                          False   \n",
+      "2                   False                                          False   \n",
+      "3                   False                                          False   \n",
+      "4                   False                                          False   \n",
+      "\n",
+      "   parental level of education_high school  \\\n",
+      "0                                    False   \n",
+      "1                                    False   \n",
+      "2                                    False   \n",
+      "3                                    False   \n",
+      "4                                    False   \n",
+      "\n",
+      "   parental level of education_master's degree  \\\n",
+      "0                                        False   \n",
+      "1                                        False   \n",
+      "2                                         True   \n",
+      "3                                        False   \n",
+      "4                                        False   \n",
+      "\n",
+      "   parental level of education_some college  \\\n",
+      "0                                     False   \n",
+      "1                                      True   \n",
+      "2                                     False   \n",
+      "3                                     False   \n",
+      "4                                      True   \n",
+      "\n",
+      "   parental level of education_some high school  lunch_standard  \\\n",
+      "0                                         False            True   \n",
+      "1                                         False            True   \n",
+      "2                                         False            True   \n",
+      "3                                         False           False   \n",
+      "4                                         False            True   \n",
+      "\n",
+      "   test preparation course_none  total_score  total_score_discrete  \n",
+      "0                          True     0.336813                     3  \n",
+      "1                         False     1.046358                     3  \n",
+      "2                          True     1.804836                     3  \n",
+      "3                          True    -1.375880                     1  \n",
+      "4                          True     0.605951                     3  \n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\New\\AppData\\Local\\Temp\\ipykernel_7044\\825875804.py:28: FutureWarning: Downcasting behavior in `replace` is deprecated and will be removed in a future version. To retain the old behavior, explicitly call `result.infer_objects(copy=False)`. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`\n",
+      "  df_encoded['total_score_discrete'] = df_encoded['total_score_discrete'].replace({'High': 3, 'Medium': 2, 'Low': 1})\n"
+     ]
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "from sklearn.model_selection import train_test_split\n",
+    "from sklearn.preprocessing import StandardScaler\n",
+    "\n",
+    "# 1. One-hot encoding для категориальных признаков\n",
+    "df_encoded = pd.get_dummies(df, columns=['gender', 'race/ethnicity', 'parental level of education', 'lunch', 'test preparation course'], drop_first=True)\n",
+    "\n",
+    "\n",
+    "# 2. Создание новых признаков\n",
+    "# - Общий балл\n",
+    "df_encoded['total_score'] = df['math score'] + df['reading score'] + df['writing score']\n",
+    "# - Категоризация баллов по математике, чтению и письму\n",
+    "def discretize_score(score):\n",
+    "     if score < 200:\n",
+    "         return 'Low'\n",
+    "     elif 250 <= score < 200:\n",
+    "         return 'Medium'\n",
+    "     else:\n",
+    "         return 'High'\n",
+    "df_encoded['total_score_discrete'] = df_encoded['total_score'].apply(lambda x: discretize_score(x))\n",
+    "\n",
+    "\n",
+    "# 3. Масштабирование числовых признаков (например, total_score и average_score)\n",
+    "scaler = StandardScaler()\n",
+    "df_encoded[['total_score']] = scaler.fit_transform(df_encoded[['total_score']])\n",
+    "\n",
+    "# Заменяем значения в total_score_discrete\n",
+    "df_encoded['total_score_discrete'] = df_encoded['total_score_discrete'].replace({'High': 3, 'Medium': 2, 'Low': 1})\n",
+    "\n",
+    "# Проверка получившихся данных\n",
+    "print(df_encoded.head())\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Конструирование признаков с помощью Featuretools"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 329,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "            gender race/ethnicity parental level of education         lunch  \\\n",
+      "student_id                                                                    \n",
+      "0           female        group B           bachelor's degree      standard   \n",
+      "1           female        group C                some college      standard   \n",
+      "2           female        group B             master's degree      standard   \n",
+      "3             male        group A          associate's degree  free/reduced   \n",
+      "4             male        group C                some college      standard   \n",
+      "\n",
+      "           test preparation course  math score  reading score  writing score  \n",
+      "student_id                                                                    \n",
+      "0                             none          72             72             74  \n",
+      "1                        completed          69             90             88  \n",
+      "2                             none          90             95             93  \n",
+      "3                             none          47             57             44  \n",
+      "4                             none          76             78             75  \n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "d:\\5semestr\\AIM\\aimvenv\\Lib\\site-packages\\featuretools\\entityset\\entityset.py:1733: UserWarning: index student_id not found in dataframe, creating new integer column\n",
+      "  warnings.warn(\n",
+      "d:\\5semestr\\AIM\\aimvenv\\Lib\\site-packages\\featuretools\\synthesis\\dfs.py:321: UnusedPrimitiveWarning: Some specified primitives were not used during DFS:\n",
+      "  agg_primitives: ['count', 'max', 'mean', 'min', 'mode', 'sum']\n",
+      "This may be caused by a using a value of max_depth that is too small, not setting interesting values, or it may indicate no compatible columns for the primitive were found in the data. If the DFS call contained multiple instances of a primitive in the list above, none of them were used.\n",
+      "  warnings.warn(warning_msg, UnusedPrimitiveWarning)\n"
+     ]
+    }
+   ],
+   "source": [
+    "import featuretools as ft\n",
+    "from woodwork.logical_types import Categorical, Integer\n",
+    "\n",
+    "# Создаем EntitySet\n",
+    "es = ft.EntitySet(id=\"students_es\")\n",
+    "\n",
+    "# Добавляем таблицу данных в EntitySet (таблица \"students\")\n",
+    "es = es.add_dataframe(\n",
+    "    dataframe_name=\"students\",\n",
+    "    dataframe=df,\n",
+    "    index=\"student_id\",\n",
+    "    logical_types={\n",
+    "        'gender': Categorical,\n",
+    "        'race/ethnicity': Categorical,\n",
+    "        'parental level of education': Categorical,\n",
+    "        'lunch': Categorical,\n",
+    "        'test preparation course': Categorical,\n",
+    "        'math score': Integer,\n",
+    "        'reading score': Integer,\n",
+    "        'writing score': Integer,\n",
+    "    }\n",
+    ")\n",
+    "\n",
+    "\n",
+    "# Теперь с помощью Deep Feature Synthesis (DFS) создадим новые признаки\n",
+    "# Применяем агрегационные и трансформационные примитивы\n",
+    "feature_matrix, feature_defs = ft.dfs(\n",
+    "    entityset=es,\n",
+    "    target_dataframe_name=\"students\",\n",
+    "    agg_primitives=[\"mean\", \"sum\", \"count\", \"mode\", \"min\", \"max\"],\n",
+    "    max_depth=1  # Уровень вложенности признаков\n",
+    ")\n",
+    "\n",
+    "# Выводим несколько новых признаков\n",
+    "print(feature_matrix.head())\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Разбиение датасета на три части: обучающую, контрольную и тестовую выборки\n",
+    "\n",
+    "Обучающая выборка (training set): используется для обучения модели. Это основная часть данных, на которой модель обучается находить зависимости.\n",
+    "\n",
+    "Валидационная выборка (validation set): используется для настройки гиперпараметров модели. Во время обучения модель проверяется на этой выборке, чтобы выбрать оптимальные параметры и избежать переобучения.\n",
+    "\n",
+    "Тестовая выборка (test set): используется для окончательной проверки модели после завершения процесса обучения. Тестовые данные не используются в процессе обучения и позволяют объективно оценить качество модели."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 330,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Размер обучающей выборки: (700, 16)\n",
+      "Размер контрольной выборки: (150, 16)\n",
+      "Размер тестовой выборки: (150, 16)\n"
+     ]
+    }
+   ],
+   "source": [
+    "from sklearn.model_selection import train_test_split\n",
+    "\n",
+    "# Предполагаем, что df — это DataFrame, содержащий все ваши данные\n",
+    "X = df_encoded.drop(columns=[\"total_score\"])  # Признаки\n",
+    "y = df_encoded[\"total_score\"]  # Несколько целевых признаков\n",
+    "\n",
+    "# Разбиение на обучающую и тестовую выборки\n",
+    "X_train, X_temp, y_train, y_temp = train_test_split(X, y, test_size=0.3, random_state=42)\n",
+    "\n",
+    "# Разбиение временной выборки на контрольную и тестовую\n",
+    "X_val, X_test, y_val, y_test = train_test_split(X_temp, y_temp, test_size=0.5, random_state=42)\n",
+    "\n",
+    "# Печатаем размеры выборок\n",
+    "print(f\"Размер обучающей выборки: {X_train.shape}\")\n",
+    "print(f\"Размер контрольной выборки: {X_val.shape}\")\n",
+    "print(f\"Размер тестовой выборки: {X_test.shape}\")\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "\n",
+    "### Оценка сбалансированности выборок\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 331,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Статистики для обучающей выборки:\n",
+      "count    700.000000\n",
+      "mean       0.034540\n",
+      "std        0.991849\n",
+      "min       -2.623699\n",
+      "25%       -0.690803\n",
+      "50%        0.043209\n",
+      "75%        0.734403\n",
+      "max        2.343111\n",
+      "Name: total_score, dtype: float64\n"
+     ]
+    }
+   ],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns\n",
+    "\n",
+    "# Оценим распределение целевого признака (total_score) для обучающей выборки\n",
+    "\n",
+    "# Создаем график для обучающей выборки\n",
+    "plt.figure(figsize=(10, 6))\n",
+    "sns.histplot(y_train, kde=True, bins=20)\n",
+    "plt.title(\"Распределение total_score для обучающей выборки\")\n",
+    "plt.xlabel(\"Total Score\")\n",
+    "plt.ylabel(\"Частота\")\n",
+    "plt.show()\n",
+    "\n",
+    "# Статистики распределения для обучающей выборки\n",
+    "print(\"Статистики для обучающей выборки:\")\n",
+    "print(y_train.describe())\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Все целевая переменная (общий балл) имеет незначительное смещение влево, что говорит о том, что большинство студентов набирают средние и ниже средние баллы. Эти данные не требуют аугментации с точки зрения смещения."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Оценка качества признаков\n",
+    "\n",
+    "Для того чтобы оценить качество каждого набора признаков по таким критериям, как предсказательная способность, скорость вычисления, надежность, корреляция и цельность, нам нужно:\n",
+    "\n",
+    "1. **Предсказательная способность**: Оценить, насколько хорошо признаки предсказывают целевые переменные, используя модель машинного обучения.\n",
+    "2. **Скорость вычисления**: Измерить время, необходимое для вычислений.\n",
+    "3. **Надежность**: Оценить устойчивость модели и признаков на кросс-валидации.\n",
+    "4. **Корреляция**: Измерить корреляцию между признаками и целевыми переменными.\n",
+    "5. **Цельность**: Проверить, насколько хорошо признаки отражают ключевые аспекты целевой переменной."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 339,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "MAE: 6.732808754961184e-16\n",
+      "R2: 1.0\n",
+      "Время обучения модели: 0.0310 секунд\n",
+      "Кросс-валидация (R2): 1.0 ± 0.0\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x800 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "                                          Feature    Importance\n",
+      "2                                   writing score  2.446705e-02\n",
+      "1                                   reading score  2.446705e-02\n",
+      "0                                      math score  2.446705e-02\n",
+      "15                           total_score_discrete  1.235990e-17\n",
+      "8   parental level of education_bachelor's degree  1.146544e-17\n",
+      "7                          race/ethnicity_group E  9.595189e-18\n",
+      "6                          race/ethnicity_group D  9.002266e-18\n",
+      "4                          race/ethnicity_group B  3.794708e-18\n",
+      "14                   test preparation course_none  7.589415e-19\n",
+      "12   parental level of education_some high school -1.036768e-18\n",
+      "11       parental level of education_some college -1.544988e-18\n",
+      "5                          race/ethnicity_group C -4.377466e-18\n",
+      "9         parental level of education_high school -6.586528e-18\n",
+      "13                                 lunch_standard -1.225148e-17\n",
+      "3                                     gender_male -1.376937e-17\n",
+      "10    parental level of education_master's degree -2.073028e-17\n"
+     ]
+    }
+   ],
+   "source": [
+    "from sklearn.linear_model import LinearRegression\n",
+    "from sklearn.metrics import mean_absolute_error, r2_score\n",
+    "from sklearn.model_selection import cross_val_score\n",
+    "import time\n",
+    "import seaborn as sns\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "\n",
+    "# 1. Оценка предсказательной способности\n",
+    "def evaluate_predictive_power(X_train, y_train, X_test, y_test):\n",
+    "    # Обучаем модель\n",
+    "    model = LinearRegression()\n",
+    "    model.fit(X_train, y_train)\n",
+    "    \n",
+    "    # Сделаем предсказания\n",
+    "    y_pred = model.predict(X_test)\n",
+    "    \n",
+    "    # Оценим метрики\n",
+    "    mae = mean_absolute_error(y_test, y_pred)\n",
+    "    r2 = r2_score(y_test, y_pred)\n",
+    "    \n",
+    "    return mae, r2\n",
+    "\n",
+    "# Оценка предсказательной способности на обучающей и тестовой выборках\n",
+    "mae, r2 = evaluate_predictive_power(X_train, y_train, X_test, y_test)\n",
+    "print(f\"MAE: {mae}\")\n",
+    "print(f\"R2: {r2}\")\n",
+    "\n",
+    "# 2. Оценка скорости вычисления\n",
+    "start_time = time.time()\n",
+    "model = LinearRegression()\n",
+    "model.fit(X_train, y_train)\n",
+    "end_time = time.time()\n",
+    "print(f\"Время обучения модели: {end_time - start_time:.4f} секунд\")\n",
+    "\n",
+    "# 3. Оценка надежности (кросс-валидация на обучающей выборке)\n",
+    "cv_scores = cross_val_score(LinearRegression(), X_train, y_train, cv=5)\n",
+    "print(f\"Кросс-валидация (R2): {cv_scores.mean()} ± {cv_scores.std()}\")\n",
+    "\n",
+    "# 4. Оценка корреляции\n",
+    "correlation_matrix = X_train.corr()\n",
+    "plt.figure(figsize=(12, 8))  # Размер фигуры: 12 дюймов по ширине и 8 дюймов по высоте\n",
+    "sns.heatmap(correlation_matrix, annot=True, cmap='coolwarm', fmt=\".2f\", linewidths=0.5)\n",
+    "plt.title(\"Корреляция между признаками на обучающей выборке\")\n",
+    "plt.show()\n",
+    "\n",
+    "\n",
+    "\n",
+    "# 5. Оценка цельности (важность признаков)\n",
+    "model = LinearRegression()\n",
+    "model.fit(X_train, y_train)\n",
+    "\n",
+    "feature_importance = model.coef_\n",
+    "feature_names = X_train.columns\n",
+    "\n",
+    "# Создаем DataFrame для отображения важности\n",
+    "importance_df = pd.DataFrame({\n",
+    "    'Feature': feature_names,\n",
+    "    'Importance': feature_importance\n",
+    "})\n",
+    "\n",
+    "# Сортируем по важности\n",
+    "importance_df = importance_df.sort_values(by='Importance', ascending=False)\n",
+    "print(importance_df)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "1. Предсказательная способность\n",
+    "R2: Результат R² равен 1.0, что означает, что модель идеально объясняет дисперсию целевой переменной в тестовой выборке. Это идеальный результат для регрессионной модели. Однако, такая высокая точность может быть признаком переобучения, особенно если модель слишком точно подгоняет данные без должной обобщающей способности.\n",
+    "MAE (Mean Absolute Error): Значение MAE близко к нулю (практически 0), что означает, что ошибка предсказания очень мала. Однако это может быть связано с идеальным R², что указывает на возможное переобучение.\n",
+    "2. Скорость вычисления\n",
+    "Время обучения: Модель обучается очень быстро (0.0310 секунд), что является хорошим признаком, особенно при использовании линейной регрессии, которая не требует больших вычислительных ресурсов.\n",
+    "3. Надежность (Кросс-валидация)\n",
+    "Кросс-валидация (R²): Значение R² также равняется 1.0 при кросс-валидации, что подтверждает, что модель показывает отличные результаты на разных подвыборках обучающих данных. Однако, как и в случае с R², это может быть показателем переобучения, так как модель стабильно дает идеальные результаты при кросс-валидации.\n",
+    "Стандартное отклонение (cv_scores.std()): Поскольку стандартное отклонение равно 0, это подтверждает, что модель стабильна на всех подвыборках и не зависит от случайности.\n",
+    "4. Корреляция\n",
+    "Корреляция между признаками: Тепловая карта показывает корреляцию между признаками, которая выглядит ожидаемо. В частности, баллы по математике, чтению и письму имеют высокую корреляцию друг с другом, что может быть полезно для предсказания общей успеваемости студентов.\n",
+    "Корреляция с целевыми переменными: Особое внимание стоит уделить корреляции между целевыми переменными и прочими признаками. Например, признаки, такие как пол и этническая принадлежность, имеют низкую корреляцию с баллами, что указывает на слабую связь этих категориальных признаков с результатами. В то же время, признак \"total_score_discrete\" сильно коррелирует с оценками (что логично, так как это синтез баллов), и это также подтверждается высокой важностью в модели.\n",
+    "5. Цельность (Важность признаков)\n",
+    "Важность признаков: Признаки \"math score\", \"reading score\" и \"writing score\" имеют самую высокую важность в модели, что логично, так как они непосредственно представляют успеваемость студента и их высокий коэффициент важности ожидаем.\n",
+    "Низкая важность для других признаков: Признаки, такие как \"gender_male\", \"lunch_standard\", и \"parental level of education_some high school\", имеют низкую важность для модели, что указывает на их слабую связь с общей успеваемостью студентов.\n",
+    "\"total_score_discrete\" имеет достаточно низкую важность по сравнению с другими признаками, что говорит о том, что этот признак, возможно, имеет зависимость с другими баллами, но его важность меньше, чем непосредственно баллы по предметам.\n",
+    "\n",
+    "### Выводы:\n",
+    "\n",
+    "**Предсказательная способность:**  \n",
+    "\n",
+    "Модель демонстрирует отличную предсказательную способность, с идеальными результатами по меткам R² и MAE. Однако это может свидетельствовать о переобучении, особенно при высоких значениях R².\n",
+    "\n",
+    "**Скорость вычисления:**  \n",
+    "\n",
+    "Модель обучается очень быстро, что является хорошим результатом и подходит для быстрой обработки данных.\n",
+    "\n",
+    "**Надежность:**\n",
+    "\n",
+    "Модель стабильна на разных подвыборках, что подтверждается результатами кросс-валидации с нулевым стандартным отклонением.\n",
+    "\n",
+    "**Корреляция:**\n",
+    "\n",
+    "Модель обнаруживает высокую корреляцию между оценками по математике, чтению и письму, но небольшую корреляцию между признаками, такими как этническая принадлежность и пол, с оценками.\n",
+    "\n",
+    "**Цельность:**\n",
+    "\n",
+    "Признаки, связанные с баллами, обладают высокой важностью для модели. В то же время, некоторые категориальные признаки, такие как \"gender\" и \"lunch\", имеют низкую важность для предсказания успеваемости."
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