{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Лабораторная 7\n",
    "Датасет: Набор данных для анализа и прогнозирования сердечного приступа"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "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>HeartDisease</th>\n",
       "      <th>BMI</th>\n",
       "      <th>Smoking</th>\n",
       "      <th>AlcoholDrinking</th>\n",
       "      <th>Stroke</th>\n",
       "      <th>PhysicalHealth</th>\n",
       "      <th>MentalHealth</th>\n",
       "      <th>DiffWalking</th>\n",
       "      <th>Sex</th>\n",
       "      <th>AgeCategory</th>\n",
       "      <th>Race</th>\n",
       "      <th>Diabetic</th>\n",
       "      <th>PhysicalActivity</th>\n",
       "      <th>GenHealth</th>\n",
       "      <th>SleepTime</th>\n",
       "      <th>Asthma</th>\n",
       "      <th>KidneyDisease</th>\n",
       "      <th>SkinCancer</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>No</td>\n",
       "      <td>16.60</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>3.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>No</td>\n",
       "      <td>Female</td>\n",
       "      <td>55-59</td>\n",
       "      <td>White</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Very good</td>\n",
       "      <td>5.0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>No</td>\n",
       "      <td>20.34</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>No</td>\n",
       "      <td>Female</td>\n",
       "      <td>80 or older</td>\n",
       "      <td>White</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Very good</td>\n",
       "      <td>7.0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>No</td>\n",
       "      <td>26.58</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>20.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>No</td>\n",
       "      <td>Male</td>\n",
       "      <td>65-69</td>\n",
       "      <td>White</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fair</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>No</td>\n",
       "      <td>24.21</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>No</td>\n",
       "      <td>Female</td>\n",
       "      <td>75-79</td>\n",
       "      <td>White</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Good</td>\n",
       "      <td>6.0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>No</td>\n",
       "      <td>23.71</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>28.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Female</td>\n",
       "      <td>40-44</td>\n",
       "      <td>White</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Very good</td>\n",
       "      <td>8.0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>319790</th>\n",
       "      <td>Yes</td>\n",
       "      <td>27.41</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Male</td>\n",
       "      <td>60-64</td>\n",
       "      <td>Hispanic</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fair</td>\n",
       "      <td>6.0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>319791</th>\n",
       "      <td>No</td>\n",
       "      <td>29.84</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>No</td>\n",
       "      <td>Male</td>\n",
       "      <td>35-39</td>\n",
       "      <td>Hispanic</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Very good</td>\n",
       "      <td>5.0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>319792</th>\n",
       "      <td>No</td>\n",
       "      <td>24.24</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>No</td>\n",
       "      <td>Female</td>\n",
       "      <td>45-49</td>\n",
       "      <td>Hispanic</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Good</td>\n",
       "      <td>6.0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>319793</th>\n",
       "      <td>No</td>\n",
       "      <td>32.81</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>No</td>\n",
       "      <td>Female</td>\n",
       "      <td>25-29</td>\n",
       "      <td>Hispanic</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Good</td>\n",
       "      <td>12.0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>319794</th>\n",
       "      <td>No</td>\n",
       "      <td>46.56</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>No</td>\n",
       "      <td>Female</td>\n",
       "      <td>80 or older</td>\n",
       "      <td>Hispanic</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Good</td>\n",
       "      <td>8.0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>319795 rows × 18 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       HeartDisease    BMI Smoking AlcoholDrinking Stroke  PhysicalHealth  \\\n",
       "0                No  16.60     Yes              No     No             3.0   \n",
       "1                No  20.34      No              No    Yes             0.0   \n",
       "2                No  26.58     Yes              No     No            20.0   \n",
       "3                No  24.21      No              No     No             0.0   \n",
       "4                No  23.71      No              No     No            28.0   \n",
       "...             ...    ...     ...             ...    ...             ...   \n",
       "319790          Yes  27.41     Yes              No     No             7.0   \n",
       "319791           No  29.84     Yes              No     No             0.0   \n",
       "319792           No  24.24      No              No     No             0.0   \n",
       "319793           No  32.81      No              No     No             0.0   \n",
       "319794           No  46.56      No              No     No             0.0   \n",
       "\n",
       "        MentalHealth DiffWalking     Sex  AgeCategory      Race Diabetic  \\\n",
       "0               30.0          No  Female        55-59     White      Yes   \n",
       "1                0.0          No  Female  80 or older     White       No   \n",
       "2               30.0          No    Male        65-69     White      Yes   \n",
       "3                0.0          No  Female        75-79     White       No   \n",
       "4                0.0         Yes  Female        40-44     White       No   \n",
       "...              ...         ...     ...          ...       ...      ...   \n",
       "319790           0.0         Yes    Male        60-64  Hispanic      Yes   \n",
       "319791           0.0          No    Male        35-39  Hispanic       No   \n",
       "319792           0.0          No  Female        45-49  Hispanic       No   \n",
       "319793           0.0          No  Female        25-29  Hispanic       No   \n",
       "319794           0.0          No  Female  80 or older  Hispanic       No   \n",
       "\n",
       "       PhysicalActivity  GenHealth  SleepTime Asthma KidneyDisease SkinCancer  \n",
       "0                   Yes  Very good        5.0    Yes            No        Yes  \n",
       "1                   Yes  Very good        7.0     No            No         No  \n",
       "2                   Yes       Fair        8.0    Yes            No         No  \n",
       "3                    No       Good        6.0     No            No        Yes  \n",
       "4                   Yes  Very good        8.0     No            No         No  \n",
       "...                 ...        ...        ...    ...           ...        ...  \n",
       "319790               No       Fair        6.0    Yes            No         No  \n",
       "319791              Yes  Very good        5.0    Yes            No         No  \n",
       "319792              Yes       Good        6.0     No            No         No  \n",
       "319793               No       Good       12.0     No            No         No  \n",
       "319794              Yes       Good        8.0     No            No         No  \n",
       "\n",
       "[319795 rows x 18 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "df = pd.read_csv(\".//static//csv//heart_2020_cleaned.csv\")\n",
    "\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Создадим лингвистические переменные и произведем их настройку\n",
    "\n",
    "Входные: BMI (индекс массы тела) и SleepTime (продолжительность сна)\n",
    "\n",
    "Выходные: PhysicalHealth (физическое здоровье)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\User\\Desktop\\aim\\aimvenv\\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 numpy as np\n",
    "import skfuzzy as fuzz\n",
    "from skfuzzy import control as ctrl\n",
    "\n",
    "bmi = ctrl.Antecedent(np.arange(df[\"BMI\"].min(), df[\"BMI\"].max() + 0.1, 0.1), \"BMI\")\n",
    "sleep_time = ctrl.Antecedent(np.arange(df[\"SleepTime\"].min(), df[\"SleepTime\"].max() + 0.1, 0.1), \"SleepTime\")\n",
    "physical_health = ctrl.Consequent(np.arange(df[\"PhysicalHealth\"].min(), df[\"PhysicalHealth\"].max() + 1, 1), \"PhysicalHealth\")\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, 35)\n",
    "\n",
    "sleep_time[\"short\"] = fuzz.zmf(sleep_time.universe, 3, 5)\n",
    "sleep_time[\"normal\"] = fuzz.trapmf(sleep_time.universe, [4, 6, 8, 9])\n",
    "sleep_time[\"long\"] = fuzz.smf(sleep_time.universe, 8, 10)\n",
    "\n",
    "physical_health[\"good\"] = fuzz.zmf(physical_health.universe, 0, 5)\n",
    "physical_health[\"moderate\"] = fuzz.trapmf(physical_health.universe, [3, 7, 15, 20])\n",
    "physical_health[\"poor\"] = fuzz.smf(physical_health.universe, 15, 30)\n",
    "\n",
    "bmi.view()\n",
    "sleep_time.view()\n",
    "physical_health.view()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Сформируем базу 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": [
    "rule1 = ctrl.Rule(bmi[\"low\"] & sleep_time[\"short\"], physical_health[\"moderate\"])\n",
    "rule2 = ctrl.Rule(bmi[\"low\"] & sleep_time[\"normal\"], physical_health[\"good\"])\n",
    "rule3 = ctrl.Rule(bmi[\"low\"] & sleep_time[\"long\"], physical_health[\"good\"])\n",
    "\n",
    "rule4 = ctrl.Rule(bmi[\"normal\"] & sleep_time[\"short\"], physical_health[\"moderate\"])\n",
    "rule5 = ctrl.Rule(bmi[\"normal\"] & sleep_time[\"normal\"], physical_health[\"good\"])\n",
    "rule6 = ctrl.Rule(bmi[\"normal\"] & sleep_time[\"long\"], physical_health[\"good\"])\n",
    "\n",
    "rule7 = ctrl.Rule(bmi[\"high\"] & sleep_time[\"short\"], physical_health[\"poor\"])\n",
    "rule8 = ctrl.Rule(bmi[\"high\"] & sleep_time[\"normal\"], physical_health[\"moderate\"])\n",
    "rule9 = ctrl.Rule(bmi[\"high\"] & sleep_time[\"long\"], physical_health[\"moderate\"])\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": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\User\\Desktop\\aim\\aimvenv\\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": [
    "health_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",
    "health_simulation = ctrl.ControlSystemSimulation(health_ctrl)\n",
    "\n",
    "health_ctrl.view()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Проверка расчета выходной переменной"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "=============\n",
      " Antecedents \n",
      "=============\n",
      "Antecedent: BMI                     = 26\n",
      "  - low                             : 0.0\n",
      "  - normal                          : 0.3333333333333333\n",
      "  - high                            : 0.02003199999999994\n",
      "Antecedent: SleepTime               = 7\n",
      "  - short                           : 0.0\n",
      "  - normal                          : 1.0\n",
      "  - long                            : 0.0\n",
      "\n",
      "=======\n",
      " Rules \n",
      "=======\n",
      "RULE #0:\n",
      "  IF BMI[low] AND SleepTime[short] THEN PhysicalHealth[moderate]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - BMI[low]                                               : 0.0\n",
      "  - SleepTime[short]                                       : 0.0\n",
      "                             BMI[low] AND SleepTime[short] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                  PhysicalHealth[moderate] : 0.0\n",
      "\n",
      "RULE #1:\n",
      "  IF BMI[low] AND SleepTime[normal] THEN PhysicalHealth[good]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - BMI[low]                                               : 0.0\n",
      "  - SleepTime[normal]                                      : 1.0\n",
      "                            BMI[low] AND SleepTime[normal] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                      PhysicalHealth[good] : 0.0\n",
      "\n",
      "RULE #2:\n",
      "  IF BMI[low] AND SleepTime[long] THEN PhysicalHealth[good]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - BMI[low]                                               : 0.0\n",
      "  - SleepTime[long]                                        : 0.0\n",
      "                              BMI[low] AND SleepTime[long] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                      PhysicalHealth[good] : 0.0\n",
      "\n",
      "RULE #3:\n",
      "  IF BMI[normal] AND SleepTime[short] THEN PhysicalHealth[moderate]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - BMI[normal]                                            : 0.3333333333333333\n",
      "  - SleepTime[short]                                       : 0.0\n",
      "                          BMI[normal] AND SleepTime[short] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                  PhysicalHealth[moderate] : 0.0\n",
      "\n",
      "RULE #4:\n",
      "  IF BMI[normal] AND SleepTime[normal] THEN PhysicalHealth[good]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - BMI[normal]                                            : 0.3333333333333333\n",
      "  - SleepTime[normal]                                      : 1.0\n",
      "                         BMI[normal] AND SleepTime[normal] = 0.3333333333333333\n",
      "  Activation (THEN-clause):\n",
      "                                      PhysicalHealth[good] : 0.3333333333333333\n",
      "\n",
      "RULE #5:\n",
      "  IF BMI[normal] AND SleepTime[long] THEN PhysicalHealth[good]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - BMI[normal]                                            : 0.3333333333333333\n",
      "  - SleepTime[long]                                        : 0.0\n",
      "                           BMI[normal] AND SleepTime[long] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                      PhysicalHealth[good] : 0.0\n",
      "\n",
      "RULE #6:\n",
      "  IF BMI[high] AND SleepTime[short] THEN PhysicalHealth[poor]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - BMI[high]                                              : 0.02003199999999994\n",
      "  - SleepTime[short]                                       : 0.0\n",
      "                            BMI[high] AND SleepTime[short] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                      PhysicalHealth[poor] : 0.0\n",
      "\n",
      "RULE #7:\n",
      "  IF BMI[high] AND SleepTime[normal] THEN PhysicalHealth[moderate]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - BMI[high]                                              : 0.02003199999999994\n",
      "  - SleepTime[normal]                                      : 1.0\n",
      "                           BMI[high] AND SleepTime[normal] = 0.02003199999999994\n",
      "  Activation (THEN-clause):\n",
      "                                  PhysicalHealth[moderate] : 0.02003199999999994\n",
      "\n",
      "RULE #8:\n",
      "  IF BMI[high] AND SleepTime[long] THEN PhysicalHealth[moderate]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - BMI[high]                                              : 0.02003199999999994\n",
      "  - SleepTime[long]                                        : 0.0\n",
      "                             BMI[high] AND SleepTime[long] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                  PhysicalHealth[moderate] : 0.0\n",
      "\n",
      "\n",
      "==============================\n",
      " Intermediaries and Conquests \n",
      "==============================\n",
      "Consequent: PhysicalHealth           = 3.9601889413098417\n",
      "  good:\n",
      "    Accumulate using accumulation_max : 0.3333333333333333\n",
      "  moderate:\n",
      "    Accumulate using accumulation_max : 0.02003199999999994\n",
      "  poor:\n",
      "    Accumulate using accumulation_max : 0.0\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "np.float64(3.9601889413098417)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "health_simulation.input[\"BMI\"] = 26\n",
    "health_simulation.input[\"SleepTime\"] = 7\n",
    "\n",
    "health_simulation.compute()\n",
    "\n",
    "health_simulation.print_state()\n",
    "\n",
    "health_simulation.output[\"PhysicalHealth\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "physical_health.view(sim=health_simulation)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Сравним результаты работы системы с реальными данными"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "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>BMI</th>\n",
       "      <th>SleepTime</th>\n",
       "      <th>PhysicalHealth</th>\n",
       "      <th>PhysicalHealth_pred</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>16.60</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.047325</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>20.34</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.490667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>26.58</td>\n",
       "      <td>8.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>7.808681</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>24.21</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.505537</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>23.71</td>\n",
       "      <td>8.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>1.490667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>28.87</td>\n",
       "      <td>12.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>11.427253</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>21.63</td>\n",
       "      <td>4.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>11.381356</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>31.64</td>\n",
       "      <td>9.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>11.381356</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>26.45</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.758991</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>40.69</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.280000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>34.30</td>\n",
       "      <td>15.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>11.281767</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>28.71</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.432978</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>28.37</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.444414</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>28.15</td>\n",
       "      <td>7.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>11.451294</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>29.29</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.411281</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>29.18</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>11.415595</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>26.26</td>\n",
       "      <td>10.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.424223</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>22.59</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.490667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>29.86</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.387517</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>18.13</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.616988</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>21.16</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.490667</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      BMI  SleepTime  PhysicalHealth  PhysicalHealth_pred\n",
       "0   16.60        5.0             3.0             2.047325\n",
       "1   20.34        7.0             0.0             1.490667\n",
       "2   26.58        8.0            20.0             7.808681\n",
       "3   24.21        6.0             0.0             1.505537\n",
       "4   23.71        8.0            28.0             1.490667\n",
       "5   28.87       12.0             6.0            11.427253\n",
       "6   21.63        4.0            15.0            11.381356\n",
       "7   31.64        9.0             5.0            11.381356\n",
       "8   26.45        5.0             0.0             6.758991\n",
       "9   40.69       10.0             0.0            11.280000\n",
       "10  34.30       15.0            30.0            11.281767\n",
       "11  28.71        5.0             0.0            11.432978\n",
       "12  28.37        8.0             0.0            11.444414\n",
       "13  28.15        7.0             7.0            11.451294\n",
       "14  29.29        5.0             0.0            11.411281\n",
       "15  29.18        6.0             1.0            11.415595\n",
       "16  26.26       10.0             5.0             5.424223\n",
       "17  22.59        8.0             0.0             1.490667\n",
       "18  29.86        5.0             0.0            11.387517\n",
       "19  18.13        8.0             0.0             1.616988\n",
       "20  21.16        8.0             0.0             1.490667"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def fuzzy_pred(row):\n",
    "    health_simulation.input[\"BMI\"] = row[\"BMI\"]\n",
    "    health_simulation.input[\"SleepTime\"] = row[\"SleepTime\"]\n",
    "    health_simulation.compute()\n",
    "    return health_simulation.output[\"PhysicalHealth\"]\n",
    "\n",
    "result = df.copy()\n",
    "\n",
    "result[\"PhysicalHealth_pred\"] = result.apply(fuzzy_pred, axis=1)\n",
    "\n",
    "result.loc[:20, [\"BMI\", \"SleepTime\", \"PhysicalHealth\", \"PhysicalHealth_pred\"]]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Оценим результаты с помощью метрик регрессии"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'RMSE': 9.902693515392837,\n",
       " 'RMAE': 2.8027515579331546,\n",
       " 'R2': -0.5512467826513943}"
      ]
     },
     "execution_count": 9,
     "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[\"PhysicalHealth\"], result[\"PhysicalHealth_pred\"])\n",
    ")\n",
    "rmetrics[\"RMAE\"] = math.sqrt(\n",
    "    metrics.mean_absolute_error(result[\"PhysicalHealth\"], result[\"PhysicalHealth_pred\"])\n",
    ")\n",
    "rmetrics[\"R2\"] = metrics.r2_score(\n",
    "    result[\"PhysicalHealth\"], result[\"PhysicalHealth_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"
   ]
  }
 ],
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