diff --git a/lab_7/lab7.ipynb b/lab_7/lab7.ipynb
new file mode 100644
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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Начало лабораторной работы"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Index(['Pregnancies', 'Glucose', 'BloodPressure', 'SkinThickness', 'Insulin',\n",
+       "       'BMI', 'DiabetesPedigreeFunction', 'Age', 'Outcome'],\n",
+       "      dtype='object')"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import numpy as np\n",
+    "import skfuzzy as fuzz\n",
+    "import matplotlib.pyplot as plt\n",
+    "import pandas as pd\n",
+    "from skfuzzy import control as ctrl\n",
+    "\n",
+    "df = pd.read_csv('C:/Users/TIGR228/Desktop/МИИ/Lab1/AIM-PIbd-31-Afanasev-S-S/static/csv/diabetes.csv')\n",
+    "#df = df[~df['bedrooms'].between(10, 34)]\n",
+    "\n",
+    "df.columns"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Определим входные и выходные переменные"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Входные X: Glucose (уровень глюкозы) и BMI (индекс массы тела)\n",
+    "\n",
+    "Выходные Y: Outcome (исход по диабету)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "glucose = ctrl.Antecedent(np.arange(0, 200, 1), \"glucose\")\n",
+    "bmi = ctrl.Antecedent(np.arange(0, 70, 1), \"bmi\")\n",
+    "outcome = ctrl.Consequent(np.arange(0, 2, 1), \"outcome\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Формирование нечетких переменных для лингвистических переменных и их визуализация"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "c:\\Users\\TIGR228\\Desktop\\МИИ\\Lab1\\AIM-PIbd-31-Afanasev-S-S\\aimenv\\Lib\\site-packages\\skfuzzy\\control\\fuzzyvariable.py:125: UserWarning: FigureCanvasAgg is non-interactive, and thus cannot be shown\n",
+      "  fig.show()\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "\n",
+    "# Определение функций принадлежности для Glucose\n",
+    "glucose['низкий'] = fuzz.trimf(glucose.universe, [0, 0, 100])\n",
+    "glucose['средний'] = fuzz.trimf(glucose.universe, [50, 100, 150])\n",
+    "glucose['высокий'] = fuzz.trimf(glucose.universe, [100, 200, 200])\n",
+    "\n",
+    "# Определение функций принадлежности для BMI\n",
+    "bmi['низкий'] = fuzz.trimf(bmi.universe, [0, 0, 25])\n",
+    "bmi['средний'] = fuzz.trimf(bmi.universe, [18.5, 25, 30])\n",
+    "bmi['высокий'] = fuzz.trimf(bmi.universe, [25, 70, 70])\n",
+    "\n",
+    "# Определение функций принадлежности для Outcome\n",
+    "outcome['нет диабета'] = fuzz.trimf(outcome.universe, [0, 0, 1])\n",
+    "outcome['есть диабет'] = fuzz.trimf(outcome.universe, [0, 1, 1])\n",
+    "\n",
+    "# Визуализация функций принадлежности\n",
+    "glucose.view()\n",
+    "bmi.view()\n",
+    "outcome.view()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Формирование и визуализация базы нечетких правил"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(<Figure size 640x480 with 1 Axes>, <Axes: >)"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "\n",
+    "# Определение правил\n",
+    "rule1 = ctrl.Rule(glucose['низкий'] & bmi['низкий'], outcome['нет диабета'])\n",
+    "rule2 = ctrl.Rule(glucose['низкий'] & bmi['средний'], outcome['нет диабета'])\n",
+    "rule3 = ctrl.Rule(glucose['низкий'] & bmi['высокий'], outcome['есть диабет'])\n",
+    "rule4 = ctrl.Rule(glucose['средний'] & bmi['низкий'], outcome['нет диабета'])\n",
+    "rule5 = ctrl.Rule(glucose['средний'] & bmi['средний'], outcome['есть диабет'])\n",
+    "rule6 = ctrl.Rule(glucose['средний'] & bmi['высокий'], outcome['есть диабет'])\n",
+    "rule7 = ctrl.Rule(glucose['высокий'] & bmi['низкий'], outcome['есть диабет'])\n",
+    "rule8 = ctrl.Rule(glucose['высокий'] & bmi['средний'], outcome['есть диабет'])\n",
+    "rule9 = ctrl.Rule(glucose['высокий'] & bmi['высокий'], outcome['есть диабет'])\n",
+    "\n",
+    "rule1.view()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Создание нечеткой системы и добавление нечетких правил в базу знаний нечеткой системы"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "outcome_ctrl = ctrl.ControlSystem(\n",
+    "    [\n",
+    "        rule1,\n",
+    "        rule2,\n",
+    "        rule3,\n",
+    "        rule4,\n",
+    "        rule5,\n",
+    "        rule6,\n",
+    "        rule7,\n",
+    "        rule8,\n",
+    "        rule9,\n",
+    "    ]\n",
+    ")\n",
+    "\n",
+    "outcomes = ctrl.ControlSystemSimulation(outcome_ctrl)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Пример расчета выходной переменной outcome на основе входных переменных glucose и bmi"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "=============\n",
+      " Antecedents \n",
+      "=============\n",
+      "Antecedent: glucose                 = 116\n",
+      "  - низкий                          : 0.0\n",
+      "  - средний                         : 0.68\n",
+      "  - высокий                         : 0.16\n",
+      "Antecedent: bmi                     = 33\n",
+      "  - низкий                          : 0.0\n",
+      "  - средний                         : 0.0\n",
+      "  - высокий                         : 0.17777777777777778\n",
+      "\n",
+      "=======\n",
+      " Rules \n",
+      "=======\n",
+      "RULE #0:\n",
+      "  IF glucose[низкий] AND bmi[низкий] THEN outcome[нет диабета]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - glucose[низкий]                                        : 0.0\n",
+      "  - bmi[низкий]                                            : 0.0\n",
+      "                           glucose[низкий] AND bmi[низкий] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                      outcome[нет диабета] : 0.0\n",
+      "\n",
+      "RULE #1:\n",
+      "  IF glucose[низкий] AND bmi[средний] THEN outcome[нет диабета]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - glucose[низкий]                                        : 0.0\n",
+      "  - bmi[средний]                                           : 0.0\n",
+      "                          glucose[низкий] AND bmi[средний] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                      outcome[нет диабета] : 0.0\n",
+      "\n",
+      "RULE #2:\n",
+      "  IF glucose[низкий] AND bmi[высокий] THEN outcome[есть диабет]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - glucose[низкий]                                        : 0.0\n",
+      "  - bmi[высокий]                                           : 0.17777777777777778\n",
+      "                          glucose[низкий] AND bmi[высокий] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                      outcome[есть диабет] : 0.0\n",
+      "\n",
+      "RULE #3:\n",
+      "  IF glucose[средний] AND bmi[низкий] THEN outcome[нет диабета]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - glucose[средний]                                       : 0.68\n",
+      "  - bmi[низкий]                                            : 0.0\n",
+      "                          glucose[средний] AND bmi[низкий] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                      outcome[нет диабета] : 0.0\n",
+      "\n",
+      "RULE #4:\n",
+      "  IF glucose[средний] AND bmi[средний] THEN outcome[есть диабет]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - glucose[средний]                                       : 0.68\n",
+      "  - bmi[средний]                                           : 0.0\n",
+      "                         glucose[средний] AND bmi[средний] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                      outcome[есть диабет] : 0.0\n",
+      "\n",
+      "RULE #5:\n",
+      "  IF glucose[средний] AND bmi[высокий] THEN outcome[есть диабет]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - glucose[средний]                                       : 0.68\n",
+      "  - bmi[высокий]                                           : 0.17777777777777778\n",
+      "                         glucose[средний] AND bmi[высокий] = 0.17777777777777778\n",
+      "  Activation (THEN-clause):\n",
+      "                                      outcome[есть диабет] : 0.17777777777777778\n",
+      "\n",
+      "RULE #6:\n",
+      "  IF glucose[высокий] AND bmi[низкий] THEN outcome[есть диабет]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - glucose[высокий]                                       : 0.16\n",
+      "  - bmi[низкий]                                            : 0.0\n",
+      "                          glucose[высокий] AND bmi[низкий] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                      outcome[есть диабет] : 0.0\n",
+      "\n",
+      "RULE #7:\n",
+      "  IF glucose[высокий] AND bmi[средний] THEN outcome[есть диабет]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - glucose[высокий]                                       : 0.16\n",
+      "  - bmi[средний]                                           : 0.0\n",
+      "                         glucose[высокий] AND bmi[средний] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                      outcome[есть диабет] : 0.0\n",
+      "\n",
+      "RULE #8:\n",
+      "  IF glucose[высокий] AND bmi[высокий] THEN outcome[есть диабет]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - glucose[высокий]                                       : 0.16\n",
+      "  - bmi[высокий]                                           : 0.17777777777777778\n",
+      "                         glucose[высокий] AND bmi[высокий] = 0.16\n",
+      "  Activation (THEN-clause):\n",
+      "                                      outcome[есть диабет] : 0.16\n",
+      "\n",
+      "\n",
+      "==============================\n",
+      " Intermediaries and Conquests \n",
+      "==============================\n",
+      "Consequent: outcome                  = 0.5429990966576332\n",
+      "  нет диабета:\n",
+      "    Accumulate using accumulation_max : 0.0\n",
+      "  есть диабет:\n",
+      "    Accumulate using accumulation_max : 0.17777777777777778\n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "np.float64(0.5429990966576332)"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "outcomes.input[\"glucose\"] = 116\n",
+    "outcomes.input[\"bmi\"] = 33\n",
+    "outcomes.compute()\n",
+    "outcomes.print_state()\n",
+    "outcomes.output[\"outcome\"]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Тестирование нечеткой системы"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "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>Glucose</th>\n",
+       "      <th>BMI</th>\n",
+       "      <th>Outcome</th>\n",
+       "      <th>Pred</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>148</td>\n",
+       "      <td>33.6</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.546095</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>85</td>\n",
+       "      <td>26.6</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.598549</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>183</td>\n",
+       "      <td>23.3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.648593</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>89</td>\n",
+       "      <td>28.1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.558266</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>137</td>\n",
+       "      <td>43.1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.585501</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>116</td>\n",
+       "      <td>25.6</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.640808</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>78</td>\n",
+       "      <td>31.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.532540</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>115</td>\n",
+       "      <td>35.3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.554757</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>197</td>\n",
+       "      <td>30.5</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.529893</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>125</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.452381</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>110</td>\n",
+       "      <td>37.6</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.566202</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>168</td>\n",
+       "      <td>38.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.568158</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>139</td>\n",
+       "      <td>27.1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.589627</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>189</td>\n",
+       "      <td>30.1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.527766</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>166</td>\n",
+       "      <td>25.8</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.637910</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    Glucose   BMI  Outcome      Pred\n",
+       "0       148  33.6        1  0.546095\n",
+       "1        85  26.6        0  0.598549\n",
+       "2       183  23.3        1  0.648593\n",
+       "3        89  28.1        0  0.558266\n",
+       "4       137  43.1        1  0.585501\n",
+       "5       116  25.6        0  0.640808\n",
+       "6        78  31.0        1  0.532540\n",
+       "7       115  35.3        0  0.554757\n",
+       "8       197  30.5        1  0.529893\n",
+       "9       125   0.0        1  0.452381\n",
+       "10      110  37.6        0  0.566202\n",
+       "11      168  38.0        1  0.568158\n",
+       "12      139  27.1        0  0.589627\n",
+       "13      189  30.1        1  0.527766\n",
+       "14      166  25.8        1  0.637910"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Функция для предсказания\n",
+    "def fuzzy_pred(row):\n",
+    "    outcomes.input['glucose'] = row['Glucose']\n",
+    "    outcomes.input['bmi'] = row['BMI']\n",
+    "    outcomes.compute()\n",
+    "    return outcomes.output['outcome']\n",
+    "\n",
+    "res = df[['Glucose', 'BMI', 'Outcome']].head(100)\n",
+    "\n",
+    "res['Pred'] = res.apply(fuzzy_pred, axis=1)\n",
+    "\n",
+    "res.head(15)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Оценка результатов на основе метрик для задачи регрессии"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'RMSE': 0.5172348603024656,\n",
+       " 'RMAE': np.float64(0.5107233852036642),\n",
+       " 'R2': -0.14771300176795843}"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import math\n",
+    "from sklearn import metrics\n",
+    "\n",
+    "# Вычисление метрик\n",
+    "rmetrics = {}\n",
+    "rmetrics[\"RMSE\"] = math.sqrt(metrics.mean_squared_error(res['Outcome'], res['Pred']))\n",
+    "rmetrics[\"RMAE\"] = metrics.mean_absolute_error(res['Outcome'], res['Pred'])\n",
+    "rmetrics[\"R2\"] = metrics.r2_score(res['Outcome'], res['Pred'])\n",
+    "\n",
+    "rmetrics"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "aimenv",
+   "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": "3.12.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}