From 2ed1523e1c0b1ae3144d763775db7b84f1c6d715 Mon Sep 17 00:00:00 2001
From: ILRodionov <elenarodionova73@gmail.com>
Date: Sat, 8 Feb 2025 22:19:23 +0400
Subject: [PATCH 1/2] lab 7 done

---
 lab_7/lab7.ipynb | 998 +++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 998 insertions(+)
 create mode 100644 lab_7/lab7.ipynb

diff --git a/lab_7/lab7.ipynb b/lab_7/lab7.ipynb
new file mode 100644
index 0000000..3b1d1de
--- /dev/null
+++ b/lab_7/lab7.ipynb
@@ -0,0 +1,998 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Загружаем датасет по варианту и выводим информацию о столбцах:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 71,
+   "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>id</th>\n",
+       "      <th>gender</th>\n",
+       "      <th>age</th>\n",
+       "      <th>hypertension</th>\n",
+       "      <th>heart_disease</th>\n",
+       "      <th>ever_married</th>\n",
+       "      <th>work_type</th>\n",
+       "      <th>Residence_type</th>\n",
+       "      <th>avg_glucose_level</th>\n",
+       "      <th>bmi</th>\n",
+       "      <th>smoking_status</th>\n",
+       "      <th>stroke</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>9046</td>\n",
+       "      <td>Male</td>\n",
+       "      <td>67.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Private</td>\n",
+       "      <td>Urban</td>\n",
+       "      <td>228.69</td>\n",
+       "      <td>36.6</td>\n",
+       "      <td>formerly smoked</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>51676</td>\n",
+       "      <td>Female</td>\n",
+       "      <td>61.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Self-employed</td>\n",
+       "      <td>Rural</td>\n",
+       "      <td>202.21</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>never smoked</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>31112</td>\n",
+       "      <td>Male</td>\n",
+       "      <td>80.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Private</td>\n",
+       "      <td>Rural</td>\n",
+       "      <td>105.92</td>\n",
+       "      <td>32.5</td>\n",
+       "      <td>never smoked</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>60182</td>\n",
+       "      <td>Female</td>\n",
+       "      <td>49.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Private</td>\n",
+       "      <td>Urban</td>\n",
+       "      <td>171.23</td>\n",
+       "      <td>34.4</td>\n",
+       "      <td>smokes</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>1665</td>\n",
+       "      <td>Female</td>\n",
+       "      <td>79.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Self-employed</td>\n",
+       "      <td>Rural</td>\n",
+       "      <td>174.12</td>\n",
+       "      <td>24.0</td>\n",
+       "      <td>never smoked</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5105</th>\n",
+       "      <td>18234</td>\n",
+       "      <td>Female</td>\n",
+       "      <td>80.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Private</td>\n",
+       "      <td>Urban</td>\n",
+       "      <td>83.75</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>never smoked</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5106</th>\n",
+       "      <td>44873</td>\n",
+       "      <td>Female</td>\n",
+       "      <td>81.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Self-employed</td>\n",
+       "      <td>Urban</td>\n",
+       "      <td>125.20</td>\n",
+       "      <td>40.0</td>\n",
+       "      <td>never smoked</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5107</th>\n",
+       "      <td>19723</td>\n",
+       "      <td>Female</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Self-employed</td>\n",
+       "      <td>Rural</td>\n",
+       "      <td>82.99</td>\n",
+       "      <td>30.6</td>\n",
+       "      <td>never smoked</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5108</th>\n",
+       "      <td>37544</td>\n",
+       "      <td>Male</td>\n",
+       "      <td>51.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Private</td>\n",
+       "      <td>Rural</td>\n",
+       "      <td>166.29</td>\n",
+       "      <td>25.6</td>\n",
+       "      <td>formerly smoked</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5109</th>\n",
+       "      <td>44679</td>\n",
+       "      <td>Female</td>\n",
+       "      <td>44.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Govt_job</td>\n",
+       "      <td>Urban</td>\n",
+       "      <td>85.28</td>\n",
+       "      <td>26.2</td>\n",
+       "      <td>Unknown</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5110 rows × 12 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "         id  gender   age  hypertension  heart_disease ever_married  \\\n",
+       "0      9046    Male  67.0             0              1          Yes   \n",
+       "1     51676  Female  61.0             0              0          Yes   \n",
+       "2     31112    Male  80.0             0              1          Yes   \n",
+       "3     60182  Female  49.0             0              0          Yes   \n",
+       "4      1665  Female  79.0             1              0          Yes   \n",
+       "...     ...     ...   ...           ...            ...          ...   \n",
+       "5105  18234  Female  80.0             1              0          Yes   \n",
+       "5106  44873  Female  81.0             0              0          Yes   \n",
+       "5107  19723  Female  35.0             0              0          Yes   \n",
+       "5108  37544    Male  51.0             0              0          Yes   \n",
+       "5109  44679  Female  44.0             0              0          Yes   \n",
+       "\n",
+       "          work_type Residence_type  avg_glucose_level   bmi   smoking_status  \\\n",
+       "0           Private          Urban             228.69  36.6  formerly smoked   \n",
+       "1     Self-employed          Rural             202.21   NaN     never smoked   \n",
+       "2           Private          Rural             105.92  32.5     never smoked   \n",
+       "3           Private          Urban             171.23  34.4           smokes   \n",
+       "4     Self-employed          Rural             174.12  24.0     never smoked   \n",
+       "...             ...            ...                ...   ...              ...   \n",
+       "5105        Private          Urban              83.75   NaN     never smoked   \n",
+       "5106  Self-employed          Urban             125.20  40.0     never smoked   \n",
+       "5107  Self-employed          Rural              82.99  30.6     never smoked   \n",
+       "5108        Private          Rural             166.29  25.6  formerly smoked   \n",
+       "5109       Govt_job          Urban              85.28  26.2          Unknown   \n",
+       "\n",
+       "      stroke  \n",
+       "0          1  \n",
+       "1          1  \n",
+       "2          1  \n",
+       "3          1  \n",
+       "4          1  \n",
+       "...      ...  \n",
+       "5105       0  \n",
+       "5106       0  \n",
+       "5107       0  \n",
+       "5108       0  \n",
+       "5109       0  \n",
+       "\n",
+       "[5110 rows x 12 columns]"
+      ]
+     },
+     "execution_count": 71,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "\n",
+    "df = pd.read_csv(\"..//..//static//csv//healthcare-dataset-stroke-data.csv\")\n",
+    "\n",
+    "df"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Заменим пустые значения в столбце bmi на медиану:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 72,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df[\"bmi\"] = df[\"bmi\"].fillna(df[\"bmi\"].median())"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Создадим лингвистические переменные\n",
+    "\n",
+    "Входные: age (возраст пациента) и bmi (индекс массы тела пациента)\n",
+    "\n",
+    "Выходные: avg_glucose_level (средний уровень глюкозы в крови)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 73,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "from skfuzzy import control as ctrl\n",
+    "\n",
+    "age = ctrl.Antecedent(np.arange(df[\"age\"].min(), df[\"age\"].max() + 1, 1), \"age\")\n",
+    "bmi = ctrl.Antecedent(np.arange(df[\"bmi\"].min(), df[\"bmi\"].max() + 0.1, 0.1), \"bmi\")\n",
+    "avg_glucose_level = ctrl.Consequent(np.arange(df[\"avg_glucose_level\"].min(), df[\"avg_glucose_level\"].max() + 0.01, 0.01), \"avg_glucose_level\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Далее произведем их настройку:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 74,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "c:\\Users\\Ilya\\Desktop\\AIM\\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": [
+    "import skfuzzy as fuzz\n",
+    "\n",
+    "age[\"young\"] = fuzz.zmf(age.universe, 7, 30)\n",
+    "age[\"middle-aged\"] = fuzz.trapmf(age.universe, [18, 30, 48, 60])\n",
+    "age[\"old\"] = fuzz.smf(age.universe, 48, 60)\n",
+    "age.view()\n",
+    "\n",
+    "bmi[\"low\"] = fuzz.zmf(bmi.universe, 12, 18)\n",
+    "bmi[\"normal\"] = fuzz.trapmf(bmi.universe, [16, 19, 24, 27])\n",
+    "bmi[\"high\"] = fuzz.smf(bmi.universe, 25, 27)\n",
+    "bmi.view()\n",
+    "\n",
+    "avg_glucose_level[\"low\"] = fuzz.zmf(avg_glucose_level.universe, 60, 75)\n",
+    "avg_glucose_level[\"normal\"] = fuzz.trapmf(avg_glucose_level.universe, [65, 75, 120, 135])\n",
+    "avg_glucose_level[\"high\"] = fuzz.smf(avg_glucose_level.universe, 120, 160)\n",
+    "avg_glucose_level.view()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Сформируем базу нечетких правил:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 75,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(<Figure size 640x480 with 1 Axes>, <Axes: >)"
+      ]
+     },
+     "execution_count": 75,
+     "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": [
+    "rule1 = ctrl.Rule(age[\"young\"] & bmi[\"low\"], avg_glucose_level[\"low\"])\n",
+    "rule2 = ctrl.Rule(age[\"young\"] & bmi[\"normal\"], avg_glucose_level[\"normal\"])\n",
+    "rule3 = ctrl.Rule(age[\"young\"] & bmi[\"high\"], avg_glucose_level[\"normal\"])\n",
+    "\n",
+    "rule4 = ctrl.Rule(age[\"middle-aged\"] & bmi[\"low\"], avg_glucose_level[\"normal\"])\n",
+    "rule5 = ctrl.Rule(age[\"middle-aged\"] & bmi[\"normal\"], avg_glucose_level[\"normal\"])\n",
+    "rule6 = ctrl.Rule(age[\"middle-aged\"] & bmi[\"high\"], avg_glucose_level[\"high\"])\n",
+    "\n",
+    "rule7 = ctrl.Rule(age[\"old\"] & bmi[\"low\"], avg_glucose_level[\"low\"])\n",
+    "rule8 = ctrl.Rule(age[\"old\"] & bmi[\"normal\"], avg_glucose_level[\"normal\"])\n",
+    "rule9 = ctrl.Rule(age[\"old\"] & bmi[\"high\"], avg_glucose_level[\"high\"])\n",
+    "\n",
+    "rule1.view()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Создадим нечеткую систему и добавим созданные нечеткие правила в ее базу знаний:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 76,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "c:\\Users\\Ilya\\Desktop\\AIM\\aimenv\\Lib\\site-packages\\skfuzzy\\control\\controlsystem.py:135: 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"
+    }
+   ],
+   "source": [
+    "glucose_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",
+    "glucose_simulation = ctrl.ControlSystemSimulation(glucose_ctrl)\n",
+    "\n",
+    "glucose_ctrl.view()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Теперь можно выполнить оценку качества полученной нечеткой системы.\n",
+    "\n",
+    "Для начала проверим работу системы на единичном примере:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 77,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "=============\n",
+      " Antecedents \n",
+      "=============\n",
+      "Antecedent: age                     = 25\n",
+      "  - young                           : 0.09479621928166351\n",
+      "  - middle-aged                     : 0.5833333333333334\n",
+      "  - old                             : 0.0\n",
+      "Antecedent: bmi                     = 26\n",
+      "  - low                             : 0.0\n",
+      "  - normal                          : 0.33333333333333337\n",
+      "  - high                            : 0.49999999999999717\n",
+      "\n",
+      "=======\n",
+      " Rules \n",
+      "=======\n",
+      "RULE #0:\n",
+      "  IF age[young] AND bmi[low] THEN avg_glucose_level[low]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - age[young]                                             : 0.09479621928166351\n",
+      "  - bmi[low]                                               : 0.0\n",
+      "                                   age[young] AND bmi[low] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                    avg_glucose_level[low] : 0.0\n",
+      "\n",
+      "RULE #1:\n",
+      "  IF age[young] AND bmi[normal] THEN avg_glucose_level[normal]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - age[young]                                             : 0.09479621928166351\n",
+      "  - bmi[normal]                                            : 0.33333333333333337\n",
+      "                                age[young] AND bmi[normal] = 0.09479621928166351\n",
+      "  Activation (THEN-clause):\n",
+      "                                 avg_glucose_level[normal] : 0.09479621928166351\n",
+      "\n",
+      "RULE #2:\n",
+      "  IF age[young] AND bmi[high] THEN avg_glucose_level[normal]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - age[young]                                             : 0.09479621928166351\n",
+      "  - bmi[high]                                              : 0.49999999999999717\n",
+      "                                  age[young] AND bmi[high] = 0.09479621928166351\n",
+      "  Activation (THEN-clause):\n",
+      "                                 avg_glucose_level[normal] : 0.09479621928166351\n",
+      "\n",
+      "RULE #3:\n",
+      "  IF age[middle-aged] AND bmi[low] THEN avg_glucose_level[normal]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - age[middle-aged]                                       : 0.5833333333333334\n",
+      "  - bmi[low]                                               : 0.0\n",
+      "                             age[middle-aged] AND bmi[low] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                 avg_glucose_level[normal] : 0.0\n",
+      "\n",
+      "RULE #4:\n",
+      "  IF age[middle-aged] AND bmi[normal] THEN avg_glucose_level[normal]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - age[middle-aged]                                       : 0.5833333333333334\n",
+      "  - bmi[normal]                                            : 0.33333333333333337\n",
+      "                          age[middle-aged] AND bmi[normal] = 0.33333333333333337\n",
+      "  Activation (THEN-clause):\n",
+      "                                 avg_glucose_level[normal] : 0.33333333333333337\n",
+      "\n",
+      "RULE #5:\n",
+      "  IF age[middle-aged] AND bmi[high] THEN avg_glucose_level[high]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - age[middle-aged]                                       : 0.5833333333333334\n",
+      "  - bmi[high]                                              : 0.49999999999999717\n",
+      "                            age[middle-aged] AND bmi[high] = 0.49999999999999717\n",
+      "  Activation (THEN-clause):\n",
+      "                                   avg_glucose_level[high] : 0.49999999999999717\n",
+      "\n",
+      "RULE #6:\n",
+      "  IF age[old] AND bmi[low] THEN avg_glucose_level[low]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - age[old]                                               : 0.0\n",
+      "  - bmi[low]                                               : 0.0\n",
+      "                                     age[old] AND bmi[low] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                    avg_glucose_level[low] : 0.0\n",
+      "\n",
+      "RULE #7:\n",
+      "  IF age[old] AND bmi[normal] THEN avg_glucose_level[normal]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - age[old]                                               : 0.0\n",
+      "  - bmi[normal]                                            : 0.33333333333333337\n",
+      "                                  age[old] AND bmi[normal] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                 avg_glucose_level[normal] : 0.0\n",
+      "\n",
+      "RULE #8:\n",
+      "  IF age[old] AND bmi[high] THEN avg_glucose_level[high]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - age[old]                                               : 0.0\n",
+      "  - bmi[high]                                              : 0.49999999999999717\n",
+      "                                    age[old] AND bmi[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                   avg_glucose_level[high] : 0.0\n",
+      "\n",
+      "\n",
+      "==============================\n",
+      " Intermediaries and Conquests \n",
+      "==============================\n",
+      "Consequent: avg_glucose_level        = 178.22779760948296\n",
+      "  low:\n",
+      "    Accumulate using accumulation_max : 0.0\n",
+      "  normal:\n",
+      "    Accumulate using accumulation_max : 0.33333333333333337\n",
+      "  high:\n",
+      "    Accumulate using accumulation_max : 0.49999999999999717\n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "np.float64(178.22779760948296)"
+      ]
+     },
+     "execution_count": 77,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "glucose_simulation.input[\"age\"] = 25\n",
+    "glucose_simulation.input[\"bmi\"] = 26\n",
+    "\n",
+    "glucose_simulation.compute()\n",
+    "\n",
+    "glucose_simulation.print_state()\n",
+    "glucose_simulation.output[\"avg_glucose_level\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 78,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "avg_glucose_level.view(sim=glucose_simulation)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Также сравним результаты работы системы с реальными данными:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 79,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def fuzzy_pred(row):\n",
+    "    glucose_simulation.input[\"age\"] = row[\"age\"]\n",
+    "    glucose_simulation.input[\"bmi\"] = row[\"bmi\"]\n",
+    "    glucose_simulation.compute()\n",
+    "    return glucose_simulation.output[\"avg_glucose_level\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 80,
+   "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>age</th>\n",
+       "      <th>bmi</th>\n",
+       "      <th>avg_glucose_level</th>\n",
+       "      <th>avg_glucose_level_pred</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>240</th>\n",
+       "      <td>66.0</td>\n",
+       "      <td>21.2</td>\n",
+       "      <td>76.46</td>\n",
+       "      <td>98.840580</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>241</th>\n",
+       "      <td>57.0</td>\n",
+       "      <td>34.5</td>\n",
+       "      <td>197.28</td>\n",
+       "      <td>204.737613</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>242</th>\n",
+       "      <td>68.0</td>\n",
+       "      <td>42.4</td>\n",
+       "      <td>233.94</td>\n",
+       "      <td>205.616976</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>243</th>\n",
+       "      <td>68.0</td>\n",
+       "      <td>40.5</td>\n",
+       "      <td>247.51</td>\n",
+       "      <td>205.616976</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>244</th>\n",
+       "      <td>57.0</td>\n",
+       "      <td>36.7</td>\n",
+       "      <td>84.96</td>\n",
+       "      <td>204.737613</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>245</th>\n",
+       "      <td>14.0</td>\n",
+       "      <td>30.9</td>\n",
+       "      <td>57.93</td>\n",
+       "      <td>99.039674</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>246</th>\n",
+       "      <td>75.0</td>\n",
+       "      <td>29.3</td>\n",
+       "      <td>78.80</td>\n",
+       "      <td>205.616976</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>247</th>\n",
+       "      <td>71.0</td>\n",
+       "      <td>28.1</td>\n",
+       "      <td>87.80</td>\n",
+       "      <td>205.616976</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>248</th>\n",
+       "      <td>78.0</td>\n",
+       "      <td>19.6</td>\n",
+       "      <td>78.81</td>\n",
+       "      <td>98.840580</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>249</th>\n",
+       "      <td>3.0</td>\n",
+       "      <td>18.0</td>\n",
+       "      <td>95.12</td>\n",
+       "      <td>99.204204</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>250</th>\n",
+       "      <td>58.0</td>\n",
+       "      <td>39.2</td>\n",
+       "      <td>87.96</td>\n",
+       "      <td>205.196699</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>251</th>\n",
+       "      <td>8.0</td>\n",
+       "      <td>17.6</td>\n",
+       "      <td>110.89</td>\n",
+       "      <td>99.254419</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>252</th>\n",
+       "      <td>70.0</td>\n",
+       "      <td>35.9</td>\n",
+       "      <td>69.04</td>\n",
+       "      <td>205.616976</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>253</th>\n",
+       "      <td>14.0</td>\n",
+       "      <td>19.1</td>\n",
+       "      <td>161.28</td>\n",
+       "      <td>99.039674</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>254</th>\n",
+       "      <td>47.0</td>\n",
+       "      <td>50.1</td>\n",
+       "      <td>210.95</td>\n",
+       "      <td>205.616976</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>255</th>\n",
+       "      <td>52.0</td>\n",
+       "      <td>17.7</td>\n",
+       "      <td>77.59</td>\n",
+       "      <td>99.263808</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>256</th>\n",
+       "      <td>75.0</td>\n",
+       "      <td>27.0</td>\n",
+       "      <td>243.53</td>\n",
+       "      <td>205.616976</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>257</th>\n",
+       "      <td>32.0</td>\n",
+       "      <td>32.3</td>\n",
+       "      <td>77.67</td>\n",
+       "      <td>205.616976</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>258</th>\n",
+       "      <td>74.0</td>\n",
+       "      <td>54.6</td>\n",
+       "      <td>205.84</td>\n",
+       "      <td>205.616976</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>259</th>\n",
+       "      <td>79.0</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>77.08</td>\n",
+       "      <td>205.616976</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>260</th>\n",
+       "      <td>79.0</td>\n",
+       "      <td>22.0</td>\n",
+       "      <td>57.08</td>\n",
+       "      <td>98.840580</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      age   bmi  avg_glucose_level  avg_glucose_level_pred\n",
+       "240  66.0  21.2              76.46               98.840580\n",
+       "241  57.0  34.5             197.28              204.737613\n",
+       "242  68.0  42.4             233.94              205.616976\n",
+       "243  68.0  40.5             247.51              205.616976\n",
+       "244  57.0  36.7              84.96              204.737613\n",
+       "245  14.0  30.9              57.93               99.039674\n",
+       "246  75.0  29.3              78.80              205.616976\n",
+       "247  71.0  28.1              87.80              205.616976\n",
+       "248  78.0  19.6              78.81               98.840580\n",
+       "249   3.0  18.0              95.12               99.204204\n",
+       "250  58.0  39.2              87.96              205.196699\n",
+       "251   8.0  17.6             110.89               99.254419\n",
+       "252  70.0  35.9              69.04              205.616976\n",
+       "253  14.0  19.1             161.28               99.039674\n",
+       "254  47.0  50.1             210.95              205.616976\n",
+       "255  52.0  17.7              77.59               99.263808\n",
+       "256  75.0  27.0             243.53              205.616976\n",
+       "257  32.0  32.3              77.67              205.616976\n",
+       "258  74.0  54.6             205.84              205.616976\n",
+       "259  79.0  35.0              77.08              205.616976\n",
+       "260  79.0  22.0              57.08               98.840580"
+      ]
+     },
+     "execution_count": 80,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "result = df.copy()\n",
+    "\n",
+    "result[\"avg_glucose_level_pred\"] = result.apply(fuzzy_pred, axis=1)\n",
+    "\n",
+    "result.loc[240:260, [\"age\", \"bmi\", \"avg_glucose_level\", \"avg_glucose_level_pred\"]]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "И оценим эти результаты с помощью метрик для задачи регрессии:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 81,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'RMSE': 83.49030705918618,\n",
+       " 'RMAE': 8.214434960116987,\n",
+       " 'R2': -2.3999770642194247}"
+      ]
+     },
+     "execution_count": 81,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import math\n",
+    "from sklearn import metrics\n",
+    "\n",
+    "rmetrics = {}\n",
+    "rmetrics[\"RMSE\"] = math.sqrt(\n",
+    "    metrics.mean_squared_error(result[\"avg_glucose_level\"], result[\"avg_glucose_level_pred\"])\n",
+    ")\n",
+    "rmetrics[\"RMAE\"] = math.sqrt(\n",
+    "    metrics.mean_absolute_error(result[\"avg_glucose_level\"], result[\"avg_glucose_level_pred\"])\n",
+    ")\n",
+    "rmetrics[\"R2\"] = metrics.r2_score(\n",
+    "    result[\"avg_glucose_level\"], result[\"avg_glucose_level_pred\"]\n",
+    ")\n",
+    "\n",
+    "rmetrics"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Как можно заметить, нечеткая система с такими переменными и настройками со своей задачей справляется плохо"
+   ]
+  }
+ ],
+ "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
+}
-- 
2.25.1


From d08bba642d2afbf2a7c4fb64fade4670f21790ec Mon Sep 17 00:00:00 2001
From: ILRodionov <elenarodionova73@gmail.com>
Date: Sat, 8 Feb 2025 22:29:02 +0400
Subject: [PATCH 2/2] add requirements

---
 lab_7/requirements.txt | Bin 0 -> 2668 bytes
 1 file changed, 0 insertions(+), 0 deletions(-)
 create mode 100644 lab_7/requirements.txt

diff --git a/lab_7/requirements.txt b/lab_7/requirements.txt
new file mode 100644
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-- 
2.25.1