AIM-PIbd-31-Bakalskaya-E-D/lab_7/lab_7.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<p style=\"margin: 15px;\">\n",
    "\n",
    "\n",
    "<ul>\n",
    "<li>Выбрать входные и выходные переменные.</li>\n",
    "<li>Выполнить настройку параметров лингвистических переменных: определить\n",
    "количество термов, типов и параметров функций принадлежности</li>\n",
    "<li>Сформировать базу нечетких правил.</li>\n",
    "<li>Выполнить оценку качества полученной нечеткой системы</li>\n",
    "</ul>\n",
    "</p>\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 5110 entries, 0 to 5109\n",
      "Data columns (total 12 columns):\n",
      " #   Column             Non-Null Count  Dtype  \n",
      "---  ------             --------------  -----  \n",
      " 0   id                 5110 non-null   int64  \n",
      " 1   gender             5110 non-null   object \n",
      " 2   age                5110 non-null   float64\n",
      " 3   hypertension       5110 non-null   int64  \n",
      " 4   heart_disease      5110 non-null   int64  \n",
      " 5   ever_married       5110 non-null   object \n",
      " 6   work_type          5110 non-null   object \n",
      " 7   Residence_type     5110 non-null   object \n",
      " 8   avg_glucose_level  5110 non-null   float64\n",
      " 9   bmi                4909 non-null   float64\n",
      " 10  smoking_status     5110 non-null   object \n",
      " 11  stroke             5110 non-null   int64  \n",
      "dtypes: float64(3), int64(4), object(5)\n",
      "memory usage: 479.2+ KB\n",
      "id                   0\n",
      "gender               0\n",
      "age                  0\n",
      "hypertension         0\n",
      "heart_disease        0\n",
      "ever_married         0\n",
      "work_type            0\n",
      "Residence_type       0\n",
      "avg_glucose_level    0\n",
      "bmi                  0\n",
      "smoking_status       0\n",
      "stroke               0\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import skfuzzy.control as control\n",
    "import skfuzzy as fuzzy\n",
    "import numpy as np\n",
    "\n",
    "\n",
    "# считаем данные и поределим входные и выходные переменные\n",
    "data = pd.read_csv(\"./csv/option4.csv\")\n",
    "data.info()\n",
    "\n",
    "data['bmi'] = data['bmi'].fillna(data['bmi'].mean())\n",
    "print(data.isnull().sum())\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<p style=\"margin: 15px;\">\n",
    "Так как мы предсказываем инсульт, то входными переменными будут самые, пожалуй, важные критерии - возраст, уровень сахара в крови, ИМТ, гипертония (ее наличие/отсутствие) и сердечный приступ (тоже его наличие/отсутствие)<br><br>а вот ВЫходной переменной будет, естесственно, сам инсульт (наличие/отсутствие)\n",
    "</p>\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {},
   "outputs": [],
   "source": [
    "age = control.Antecedent(np.arange(0, 101, 1), 'age') # возраст от 0 до 100 с шагом 1 год и т.д.\n",
    "glucose = control.Antecedent(np.arange(50, 301, 1), 'glucose')\n",
    "bmi = control.Antecedent(np.arange(10, 50, 0.1), 'bmi')\n",
    "hypertension = control.Antecedent(np.arange(0, 2, 0.1), 'hypertension')\n",
    "heart_disease = control.Antecedent(np.arange(0, 2, 0.1), 'heart_disease')\n",
    "\n",
    "# а теперь выходная переменная (Consequent)\n",
    "stroke_risk = control.Consequent(np.arange(0, 1.1, 0.1), 'stroke_risk')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<p style=\"margin: 15px; text-align: center;\">\n",
    "НАКОНЕЦ Я УСТАНОВИЛА ВСЕ ПАКЕТЫ етить его\n",
    "</p>\n",
    "\n",
    "<p style=\"margin: 15px;\">\n",
    "теперь самое время определить нечеткие переменные, которые сложатся... в лингвистические\n",
    "</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "d:\\code\\mai\\labs\\AIM-PIbd-31-Bakalskaya-E-D\\lab_7\\.venv\\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"
    },
    {
     "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 matplotlib.pyplot as plt\n",
    "\n",
    "# возраст\n",
    "age['young'] = fuzzy.zmf(age.universe, 0, 30)\n",
    "age['middle'] = fuzzy.trapmf(age.universe, [18, 20, 30, 40])\n",
    "age['old'] = fuzzy.trapmf(age.universe, [40, 50, 60, 70])\n",
    "age['aged'] = fuzzy.smf(age.universe, 60, 100)  \n",
    "\n",
    "# сахар\n",
    "glucose['low'] = fuzzy.zmf(glucose.universe, 50, 80)\n",
    "glucose['normal'] = fuzzy.trapmf(glucose.universe, [70, 80, 90, 100])\n",
    "glucose['high'] = fuzzy.smf(glucose.universe, 100, 300)\n",
    "\n",
    "# ИМТ\n",
    "bmi['low'] = fuzzy.zmf(bmi.universe, 0, 19)\n",
    "bmi['normal'] = fuzzy.trimf(bmi.universe, [18, 20, 25])\n",
    "bmi['high'] = fuzzy.smf(bmi.universe, 25, 50)\n",
    "\n",
    "# гипертония\n",
    "hypertension['low'] = fuzzy.zmf(hypertension.universe, 0, 0.6)\n",
    "hypertension['high'] = fuzzy.smf(hypertension.universe, 0.4, 1.0)\n",
    "\n",
    "# пердечный сриступ\n",
    "heart_disease['low'] = fuzzy.zmf(heart_disease.universe, 0, 0.6)\n",
    "heart_disease['high'] = fuzzy.smf(heart_disease.universe, 0.4, 1.0)\n",
    "\n",
    "#риск инсульта\n",
    "stroke_risk['low'] = fuzzy.zmf(stroke_risk.universe, 0, 0.4)\n",
    "stroke_risk['medium'] = fuzzy.trimf(stroke_risk.universe, [0.3, 0.5, 0.7])\n",
    "stroke_risk['high'] = fuzzy.smf(stroke_risk.universe, 0.6, 1.0)\n",
    "\n",
    "\n",
    "age.view()\n",
    "glucose.view()\n",
    "bmi.view()\n",
    "hypertension.view()\n",
    "heart_disease.view()\n",
    "stroke_risk.view()\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<p style=\"margin: 15px;\">\n",
    "а теперь формируем базу нечетких правил :D\n",
    "</p>\n",
    "\n",
    "\n",
    "<style>\n",
    "  .blur-text {\n",
    "    filter: blur(3px);\n",
    "    transition: filter 0.3s ease-in-out;\n",
    "    cursor: pointer;\n",
    "  }\n",
    "\n",
    "  .blur-text.clear {\n",
    "    filter: blur(0);\n",
    "  }\n",
    "</style>\n",
    "\n",
    "<p class=\"blur-text\" onclick=\"this.classList.toggle('clear')\" style=\"margin: 15px;\">\n",
    "  ну.... с написанием правил мне чат гпт помог, ну а что, у меня 5 входных переменных... я не знала, на что наткнусь, когда дойду до этого момента, поэтому... спасибо чату\n",
    "</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {},
   "outputs": [],
   "source": [
    "rules = []\n",
    "\n",
    "ages = ['young', 'middle', 'old', 'aged']\n",
    "hypertension_levels = ['low', 'high']\n",
    "glucose_levels = ['low', 'normal', 'high']\n",
    "bmi_levels = ['low', 'normal', 'high']\n",
    "heart_disease_levels = ['low', 'high']\n",
    "\n",
    "for ag in ages:\n",
    "    for hl in hypertension_levels:\n",
    "        for gl in glucose_levels:\n",
    "            for bm in bmi_levels:\n",
    "                for hd in heart_disease_levels:\n",
    "                    # Определяем уровень риска\n",
    "                    if ag in ['aged', 'old'] and hl == 'high' and gl == 'high' and bm == 'high' and hd == 'high':\n",
    "                        risk = 'high'\n",
    "                    elif ag in ['middle', 'old'] and hl == 'high' and gl == 'high' and bm in ['normal', 'high']:\n",
    "                        risk = 'high'\n",
    "                    elif ag == 'young' and hl == 'low' and gl == 'low' and bm == 'low' and hd == 'low':\n",
    "                        risk = 'low'\n",
    "                    elif gl == 'normal' and bm == 'normal' and hd == 'low':\n",
    "                        risk = 'low'\n",
    "                    elif ag == 'middle' and hl == 'low' and gl == 'low' and bm == 'low':\n",
    "                        risk = 'low'\n",
    "                    else:\n",
    "                        risk = 'medium'\n",
    "                    \n",
    "                    # Создаем правило\n",
    "                    rule = control.Rule(\n",
    "                        age[ag] & hypertension[hl] & glucose[gl] & bmi[bm] & heart_disease[hd],\n",
    "                        stroke_risk[risk]\n",
    "                    )\n",
    "                    rules.append(rule)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "d:\\code\\mai\\labs\\AIM-PIbd-31-Bakalskaya-E-D\\lab_7\\.venv\\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": [
    "stroke_ctrl = control.ControlSystem(\n",
    "    rules\n",
    ")\n",
    "\n",
    "stroke_simulation = control.ControlSystemSimulation(stroke_ctrl)\n",
    "stroke_ctrl.view()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "=============\n",
      " Antecedents \n",
      "=============\n",
      "Antecedent: age                     = 72\n",
      "  - young                           : 0.0\n",
      "  - middle                          : 0.0\n",
      "  - old                             : 0.0\n",
      "  - aged                            : 0.18\n",
      "Antecedent: hypertension            = 1\n",
      "  - low                             : 0.0\n",
      "  - high                            : 1.0\n",
      "Antecedent: glucose                 = 220\n",
      "  - low                             : 0.0\n",
      "  - normal                          : 0.0\n",
      "  - high                            : 0.6799999999999999\n",
      "Antecedent: bmi                     = 30\n",
      "  - low                             : 0.0\n",
      "  - normal                          : 0.0\n",
      "  - high                            : 0.08000000000000002\n",
      "Antecedent: heart_disease           = 0\n",
      "  - low                             : 1.0\n",
      "  - high                            : 0.0\n",
      "\n",
      "=======\n",
      " Rules \n",
      "=======\n",
      "RULE #0:\n",
      "  IF (((age[young] AND hypertension[low]) AND glucose[low]) AND bmi[low]) AND heart_disease[low] THEN stroke_risk[low]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[young]                                             : 0.0\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[low]                                           : 0.0\n",
      "  - bmi[low]                                               : 0.0\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[young] AND hypertension[low]) AND glucose[low]) AND bmi[low]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                          stroke_risk[low] : 0.0\n",
      "\n",
      "RULE #1:\n",
      "  IF (((age[young] AND hypertension[low]) AND glucose[low]) AND bmi[low]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[young]                                             : 0.0\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[low]                                           : 0.0\n",
      "  - bmi[low]                                               : 0.0\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[young] AND hypertension[low]) AND glucose[low]) AND bmi[low]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #2:\n",
      "  IF (((age[young] AND hypertension[low]) AND glucose[low]) AND bmi[normal]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[young]                                             : 0.0\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[low]                                           : 0.0\n",
      "  - bmi[normal]                                            : 0.0\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[young] AND hypertension[low]) AND glucose[low]) AND bmi[normal]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #3:\n",
      "  IF (((age[young] AND hypertension[low]) AND glucose[low]) AND bmi[normal]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[young]                                             : 0.0\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[low]                                           : 0.0\n",
      "  - bmi[normal]                                            : 0.0\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[young] AND hypertension[low]) AND glucose[low]) AND bmi[normal]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #4:\n",
      "  IF (((age[young] AND hypertension[low]) AND glucose[low]) AND bmi[high]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[young]                                             : 0.0\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[low]                                           : 0.0\n",
      "  - bmi[high]                                              : 0.08000000000000002\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[young] AND hypertension[low]) AND glucose[low]) AND bmi[high]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #5:\n",
      "  IF (((age[young] AND hypertension[low]) AND glucose[low]) AND bmi[high]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[young]                                             : 0.0\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[low]                                           : 0.0\n",
      "  - bmi[high]                                              : 0.08000000000000002\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[young] AND hypertension[low]) AND glucose[low]) AND bmi[high]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #6:\n",
      "  IF (((age[young] AND hypertension[low]) AND glucose[normal]) AND bmi[low]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[young]                                             : 0.0\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[normal]                                        : 0.0\n",
      "  - bmi[low]                                               : 0.0\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[young] AND hypertension[low]) AND glucose[normal]) AND bmi[low]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #7:\n",
      "  IF (((age[young] AND hypertension[low]) AND glucose[normal]) AND bmi[low]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[young]                                             : 0.0\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[normal]                                        : 0.0\n",
      "  - bmi[low]                                               : 0.0\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[young] AND hypertension[low]) AND glucose[normal]) AND bmi[low]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #8:\n",
      "  IF (((age[young] AND hypertension[low]) AND glucose[normal]) AND bmi[normal]) AND heart_disease[low] THEN stroke_risk[low]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[young]                                             : 0.0\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[normal]                                        : 0.0\n",
      "  - bmi[normal]                                            : 0.0\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[young] AND hypertension[low]) AND glucose[normal]) AND bmi[normal]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                          stroke_risk[low] : 0.0\n",
      "\n",
      "RULE #9:\n",
      "  IF (((age[young] AND hypertension[low]) AND glucose[normal]) AND bmi[normal]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[young]                                             : 0.0\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[normal]                                        : 0.0\n",
      "  - bmi[normal]                                            : 0.0\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[young] AND hypertension[low]) AND glucose[normal]) AND bmi[normal]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #10:\n",
      "  IF (((age[young] AND hypertension[low]) AND glucose[normal]) AND bmi[high]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[young]                                             : 0.0\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[normal]                                        : 0.0\n",
      "  - bmi[high]                                              : 0.08000000000000002\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[young] AND hypertension[low]) AND glucose[normal]) AND bmi[high]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #11:\n",
      "  IF (((age[young] AND hypertension[low]) AND glucose[normal]) AND bmi[high]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[young]                                             : 0.0\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[normal]                                        : 0.0\n",
      "  - bmi[high]                                              : 0.08000000000000002\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[young] AND hypertension[low]) AND glucose[normal]) AND bmi[high]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #12:\n",
      "  IF (((age[young] AND hypertension[low]) AND glucose[high]) AND bmi[low]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[young]                                             : 0.0\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[high]                                          : 0.6799999999999999\n",
      "  - bmi[low]                                               : 0.0\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[young] AND hypertension[low]) AND glucose[high]) AND bmi[low]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #13:\n",
      "  IF (((age[young] AND hypertension[low]) AND glucose[high]) AND bmi[low]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[young]                                             : 0.0\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[high]                                          : 0.6799999999999999\n",
      "  - bmi[low]                                               : 0.0\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[young] AND hypertension[low]) AND glucose[high]) AND bmi[low]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #14:\n",
      "  IF (((age[young] AND hypertension[low]) AND glucose[high]) AND bmi[normal]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[young]                                             : 0.0\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[high]                                          : 0.6799999999999999\n",
      "  - bmi[normal]                                            : 0.0\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[young] AND hypertension[low]) AND glucose[high]) AND bmi[normal]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #15:\n",
      "  IF (((age[young] AND hypertension[low]) AND glucose[high]) AND bmi[normal]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[young]                                             : 0.0\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[high]                                          : 0.6799999999999999\n",
      "  - bmi[normal]                                            : 0.0\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[young] AND hypertension[low]) AND glucose[high]) AND bmi[normal]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #16:\n",
      "  IF (((age[young] AND hypertension[low]) AND glucose[high]) AND bmi[high]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[young]                                             : 0.0\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[high]                                          : 0.6799999999999999\n",
      "  - bmi[high]                                              : 0.08000000000000002\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[young] AND hypertension[low]) AND glucose[high]) AND bmi[high]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #17:\n",
      "  IF (((age[young] AND hypertension[low]) AND glucose[high]) AND bmi[high]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[young]                                             : 0.0\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[high]                                          : 0.6799999999999999\n",
      "  - bmi[high]                                              : 0.08000000000000002\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[young] AND hypertension[low]) AND glucose[high]) AND bmi[high]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #18:\n",
      "  IF (((age[young] AND hypertension[high]) AND glucose[low]) AND bmi[low]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[young]                                             : 0.0\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[low]                                           : 0.0\n",
      "  - bmi[low]                                               : 0.0\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[young] AND hypertension[high]) AND glucose[low]) AND bmi[low]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #19:\n",
      "  IF (((age[young] AND hypertension[high]) AND glucose[low]) AND bmi[low]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[young]                                             : 0.0\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[low]                                           : 0.0\n",
      "  - bmi[low]                                               : 0.0\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[young] AND hypertension[high]) AND glucose[low]) AND bmi[low]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #20:\n",
      "  IF (((age[young] AND hypertension[high]) AND glucose[low]) AND bmi[normal]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[young]                                             : 0.0\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[low]                                           : 0.0\n",
      "  - bmi[normal]                                            : 0.0\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[young] AND hypertension[high]) AND glucose[low]) AND bmi[normal]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #21:\n",
      "  IF (((age[young] AND hypertension[high]) AND glucose[low]) AND bmi[normal]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[young]                                             : 0.0\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[low]                                           : 0.0\n",
      "  - bmi[normal]                                            : 0.0\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[young] AND hypertension[high]) AND glucose[low]) AND bmi[normal]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #22:\n",
      "  IF (((age[young] AND hypertension[high]) AND glucose[low]) AND bmi[high]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[young]                                             : 0.0\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[low]                                           : 0.0\n",
      "  - bmi[high]                                              : 0.08000000000000002\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[young] AND hypertension[high]) AND glucose[low]) AND bmi[high]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #23:\n",
      "  IF (((age[young] AND hypertension[high]) AND glucose[low]) AND bmi[high]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[young]                                             : 0.0\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[low]                                           : 0.0\n",
      "  - bmi[high]                                              : 0.08000000000000002\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[young] AND hypertension[high]) AND glucose[low]) AND bmi[high]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #24:\n",
      "  IF (((age[young] AND hypertension[high]) AND glucose[normal]) AND bmi[low]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[young]                                             : 0.0\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[normal]                                        : 0.0\n",
      "  - bmi[low]                                               : 0.0\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[young] AND hypertension[high]) AND glucose[normal]) AND bmi[low]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #25:\n",
      "  IF (((age[young] AND hypertension[high]) AND glucose[normal]) AND bmi[low]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[young]                                             : 0.0\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[normal]                                        : 0.0\n",
      "  - bmi[low]                                               : 0.0\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[young] AND hypertension[high]) AND glucose[normal]) AND bmi[low]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #26:\n",
      "  IF (((age[young] AND hypertension[high]) AND glucose[normal]) AND bmi[normal]) AND heart_disease[low] THEN stroke_risk[low]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[young]                                             : 0.0\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[normal]                                        : 0.0\n",
      "  - bmi[normal]                                            : 0.0\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[young] AND hypertension[high]) AND glucose[normal]) AND bmi[normal]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                          stroke_risk[low] : 0.0\n",
      "\n",
      "RULE #27:\n",
      "  IF (((age[young] AND hypertension[high]) AND glucose[normal]) AND bmi[normal]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[young]                                             : 0.0\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[normal]                                        : 0.0\n",
      "  - bmi[normal]                                            : 0.0\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[young] AND hypertension[high]) AND glucose[normal]) AND bmi[normal]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #28:\n",
      "  IF (((age[young] AND hypertension[high]) AND glucose[normal]) AND bmi[high]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[young]                                             : 0.0\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[normal]                                        : 0.0\n",
      "  - bmi[high]                                              : 0.08000000000000002\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[young] AND hypertension[high]) AND glucose[normal]) AND bmi[high]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #29:\n",
      "  IF (((age[young] AND hypertension[high]) AND glucose[normal]) AND bmi[high]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[young]                                             : 0.0\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[normal]                                        : 0.0\n",
      "  - bmi[high]                                              : 0.08000000000000002\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[young] AND hypertension[high]) AND glucose[normal]) AND bmi[high]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #30:\n",
      "  IF (((age[young] AND hypertension[high]) AND glucose[high]) AND bmi[low]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[young]                                             : 0.0\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[high]                                          : 0.6799999999999999\n",
      "  - bmi[low]                                               : 0.0\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[young] AND hypertension[high]) AND glucose[high]) AND bmi[low]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #31:\n",
      "  IF (((age[young] AND hypertension[high]) AND glucose[high]) AND bmi[low]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[young]                                             : 0.0\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[high]                                          : 0.6799999999999999\n",
      "  - bmi[low]                                               : 0.0\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[young] AND hypertension[high]) AND glucose[high]) AND bmi[low]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #32:\n",
      "  IF (((age[young] AND hypertension[high]) AND glucose[high]) AND bmi[normal]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[young]                                             : 0.0\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[high]                                          : 0.6799999999999999\n",
      "  - bmi[normal]                                            : 0.0\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[young] AND hypertension[high]) AND glucose[high]) AND bmi[normal]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #33:\n",
      "  IF (((age[young] AND hypertension[high]) AND glucose[high]) AND bmi[normal]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[young]                                             : 0.0\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[high]                                          : 0.6799999999999999\n",
      "  - bmi[normal]                                            : 0.0\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[young] AND hypertension[high]) AND glucose[high]) AND bmi[normal]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #34:\n",
      "  IF (((age[young] AND hypertension[high]) AND glucose[high]) AND bmi[high]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[young]                                             : 0.0\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[high]                                          : 0.6799999999999999\n",
      "  - bmi[high]                                              : 0.08000000000000002\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[young] AND hypertension[high]) AND glucose[high]) AND bmi[high]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #35:\n",
      "  IF (((age[young] AND hypertension[high]) AND glucose[high]) AND bmi[high]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[young]                                             : 0.0\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[high]                                          : 0.6799999999999999\n",
      "  - bmi[high]                                              : 0.08000000000000002\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[young] AND hypertension[high]) AND glucose[high]) AND bmi[high]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #36:\n",
      "  IF (((age[middle] AND hypertension[low]) AND glucose[low]) AND bmi[low]) AND heart_disease[low] THEN stroke_risk[low]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[middle]                                            : 0.0\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[low]                                           : 0.0\n",
      "  - bmi[low]                                               : 0.0\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[middle] AND hypertension[low]) AND glucose[low]) AND bmi[low]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                          stroke_risk[low] : 0.0\n",
      "\n",
      "RULE #37:\n",
      "  IF (((age[middle] AND hypertension[low]) AND glucose[low]) AND bmi[low]) AND heart_disease[high] THEN stroke_risk[low]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[middle]                                            : 0.0\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[low]                                           : 0.0\n",
      "  - bmi[low]                                               : 0.0\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[middle] AND hypertension[low]) AND glucose[low]) AND bmi[low]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                          stroke_risk[low] : 0.0\n",
      "\n",
      "RULE #38:\n",
      "  IF (((age[middle] AND hypertension[low]) AND glucose[low]) AND bmi[normal]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[middle]                                            : 0.0\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[low]                                           : 0.0\n",
      "  - bmi[normal]                                            : 0.0\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[middle] AND hypertension[low]) AND glucose[low]) AND bmi[normal]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #39:\n",
      "  IF (((age[middle] AND hypertension[low]) AND glucose[low]) AND bmi[normal]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[middle]                                            : 0.0\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[low]                                           : 0.0\n",
      "  - bmi[normal]                                            : 0.0\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[middle] AND hypertension[low]) AND glucose[low]) AND bmi[normal]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #40:\n",
      "  IF (((age[middle] AND hypertension[low]) AND glucose[low]) AND bmi[high]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[middle]                                            : 0.0\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[low]                                           : 0.0\n",
      "  - bmi[high]                                              : 0.08000000000000002\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[middle] AND hypertension[low]) AND glucose[low]) AND bmi[high]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #41:\n",
      "  IF (((age[middle] AND hypertension[low]) AND glucose[low]) AND bmi[high]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[middle]                                            : 0.0\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[low]                                           : 0.0\n",
      "  - bmi[high]                                              : 0.08000000000000002\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[middle] AND hypertension[low]) AND glucose[low]) AND bmi[high]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #42:\n",
      "  IF (((age[middle] AND hypertension[low]) AND glucose[normal]) AND bmi[low]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[middle]                                            : 0.0\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[normal]                                        : 0.0\n",
      "  - bmi[low]                                               : 0.0\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[middle] AND hypertension[low]) AND glucose[normal]) AND bmi[low]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #43:\n",
      "  IF (((age[middle] AND hypertension[low]) AND glucose[normal]) AND bmi[low]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[middle]                                            : 0.0\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[normal]                                        : 0.0\n",
      "  - bmi[low]                                               : 0.0\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[middle] AND hypertension[low]) AND glucose[normal]) AND bmi[low]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #44:\n",
      "  IF (((age[middle] AND hypertension[low]) AND glucose[normal]) AND bmi[normal]) AND heart_disease[low] THEN stroke_risk[low]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[middle]                                            : 0.0\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[normal]                                        : 0.0\n",
      "  - bmi[normal]                                            : 0.0\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[middle] AND hypertension[low]) AND glucose[normal]) AND bmi[normal]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                          stroke_risk[low] : 0.0\n",
      "\n",
      "RULE #45:\n",
      "  IF (((age[middle] AND hypertension[low]) AND glucose[normal]) AND bmi[normal]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[middle]                                            : 0.0\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[normal]                                        : 0.0\n",
      "  - bmi[normal]                                            : 0.0\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[middle] AND hypertension[low]) AND glucose[normal]) AND bmi[normal]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #46:\n",
      "  IF (((age[middle] AND hypertension[low]) AND glucose[normal]) AND bmi[high]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[middle]                                            : 0.0\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[normal]                                        : 0.0\n",
      "  - bmi[high]                                              : 0.08000000000000002\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[middle] AND hypertension[low]) AND glucose[normal]) AND bmi[high]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #47:\n",
      "  IF (((age[middle] AND hypertension[low]) AND glucose[normal]) AND bmi[high]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[middle]                                            : 0.0\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[normal]                                        : 0.0\n",
      "  - bmi[high]                                              : 0.08000000000000002\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[middle] AND hypertension[low]) AND glucose[normal]) AND bmi[high]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #48:\n",
      "  IF (((age[middle] AND hypertension[low]) AND glucose[high]) AND bmi[low]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[middle]                                            : 0.0\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[high]                                          : 0.6799999999999999\n",
      "  - bmi[low]                                               : 0.0\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[middle] AND hypertension[low]) AND glucose[high]) AND bmi[low]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #49:\n",
      "  IF (((age[middle] AND hypertension[low]) AND glucose[high]) AND bmi[low]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[middle]                                            : 0.0\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[high]                                          : 0.6799999999999999\n",
      "  - bmi[low]                                               : 0.0\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[middle] AND hypertension[low]) AND glucose[high]) AND bmi[low]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #50:\n",
      "  IF (((age[middle] AND hypertension[low]) AND glucose[high]) AND bmi[normal]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[middle]                                            : 0.0\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[high]                                          : 0.6799999999999999\n",
      "  - bmi[normal]                                            : 0.0\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[middle] AND hypertension[low]) AND glucose[high]) AND bmi[normal]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #51:\n",
      "  IF (((age[middle] AND hypertension[low]) AND glucose[high]) AND bmi[normal]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[middle]                                            : 0.0\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[high]                                          : 0.6799999999999999\n",
      "  - bmi[normal]                                            : 0.0\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[middle] AND hypertension[low]) AND glucose[high]) AND bmi[normal]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #52:\n",
      "  IF (((age[middle] AND hypertension[low]) AND glucose[high]) AND bmi[high]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[middle]                                            : 0.0\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[high]                                          : 0.6799999999999999\n",
      "  - bmi[high]                                              : 0.08000000000000002\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[middle] AND hypertension[low]) AND glucose[high]) AND bmi[high]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #53:\n",
      "  IF (((age[middle] AND hypertension[low]) AND glucose[high]) AND bmi[high]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[middle]                                            : 0.0\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[high]                                          : 0.6799999999999999\n",
      "  - bmi[high]                                              : 0.08000000000000002\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[middle] AND hypertension[low]) AND glucose[high]) AND bmi[high]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #54:\n",
      "  IF (((age[middle] AND hypertension[high]) AND glucose[low]) AND bmi[low]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[middle]                                            : 0.0\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[low]                                           : 0.0\n",
      "  - bmi[low]                                               : 0.0\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[middle] AND hypertension[high]) AND glucose[low]) AND bmi[low]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #55:\n",
      "  IF (((age[middle] AND hypertension[high]) AND glucose[low]) AND bmi[low]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[middle]                                            : 0.0\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[low]                                           : 0.0\n",
      "  - bmi[low]                                               : 0.0\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[middle] AND hypertension[high]) AND glucose[low]) AND bmi[low]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #56:\n",
      "  IF (((age[middle] AND hypertension[high]) AND glucose[low]) AND bmi[normal]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[middle]                                            : 0.0\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[low]                                           : 0.0\n",
      "  - bmi[normal]                                            : 0.0\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[middle] AND hypertension[high]) AND glucose[low]) AND bmi[normal]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #57:\n",
      "  IF (((age[middle] AND hypertension[high]) AND glucose[low]) AND bmi[normal]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[middle]                                            : 0.0\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[low]                                           : 0.0\n",
      "  - bmi[normal]                                            : 0.0\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[middle] AND hypertension[high]) AND glucose[low]) AND bmi[normal]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #58:\n",
      "  IF (((age[middle] AND hypertension[high]) AND glucose[low]) AND bmi[high]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[middle]                                            : 0.0\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[low]                                           : 0.0\n",
      "  - bmi[high]                                              : 0.08000000000000002\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[middle] AND hypertension[high]) AND glucose[low]) AND bmi[high]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #59:\n",
      "  IF (((age[middle] AND hypertension[high]) AND glucose[low]) AND bmi[high]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[middle]                                            : 0.0\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[low]                                           : 0.0\n",
      "  - bmi[high]                                              : 0.08000000000000002\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[middle] AND hypertension[high]) AND glucose[low]) AND bmi[high]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #60:\n",
      "  IF (((age[middle] AND hypertension[high]) AND glucose[normal]) AND bmi[low]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[middle]                                            : 0.0\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[normal]                                        : 0.0\n",
      "  - bmi[low]                                               : 0.0\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[middle] AND hypertension[high]) AND glucose[normal]) AND bmi[low]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #61:\n",
      "  IF (((age[middle] AND hypertension[high]) AND glucose[normal]) AND bmi[low]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[middle]                                            : 0.0\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[normal]                                        : 0.0\n",
      "  - bmi[low]                                               : 0.0\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[middle] AND hypertension[high]) AND glucose[normal]) AND bmi[low]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #62:\n",
      "  IF (((age[middle] AND hypertension[high]) AND glucose[normal]) AND bmi[normal]) AND heart_disease[low] THEN stroke_risk[low]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[middle]                                            : 0.0\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[normal]                                        : 0.0\n",
      "  - bmi[normal]                                            : 0.0\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[middle] AND hypertension[high]) AND glucose[normal]) AND bmi[normal]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                          stroke_risk[low] : 0.0\n",
      "\n",
      "RULE #63:\n",
      "  IF (((age[middle] AND hypertension[high]) AND glucose[normal]) AND bmi[normal]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[middle]                                            : 0.0\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[normal]                                        : 0.0\n",
      "  - bmi[normal]                                            : 0.0\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[middle] AND hypertension[high]) AND glucose[normal]) AND bmi[normal]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #64:\n",
      "  IF (((age[middle] AND hypertension[high]) AND glucose[normal]) AND bmi[high]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[middle]                                            : 0.0\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[normal]                                        : 0.0\n",
      "  - bmi[high]                                              : 0.08000000000000002\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[middle] AND hypertension[high]) AND glucose[normal]) AND bmi[high]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #65:\n",
      "  IF (((age[middle] AND hypertension[high]) AND glucose[normal]) AND bmi[high]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[middle]                                            : 0.0\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[normal]                                        : 0.0\n",
      "  - bmi[high]                                              : 0.08000000000000002\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[middle] AND hypertension[high]) AND glucose[normal]) AND bmi[high]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #66:\n",
      "  IF (((age[middle] AND hypertension[high]) AND glucose[high]) AND bmi[low]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[middle]                                            : 0.0\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[high]                                          : 0.6799999999999999\n",
      "  - bmi[low]                                               : 0.0\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[middle] AND hypertension[high]) AND glucose[high]) AND bmi[low]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #67:\n",
      "  IF (((age[middle] AND hypertension[high]) AND glucose[high]) AND bmi[low]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[middle]                                            : 0.0\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[high]                                          : 0.6799999999999999\n",
      "  - bmi[low]                                               : 0.0\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[middle] AND hypertension[high]) AND glucose[high]) AND bmi[low]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #68:\n",
      "  IF (((age[middle] AND hypertension[high]) AND glucose[high]) AND bmi[normal]) AND heart_disease[low] THEN stroke_risk[high]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[middle]                                            : 0.0\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[high]                                          : 0.6799999999999999\n",
      "  - bmi[normal]                                            : 0.0\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[middle] AND hypertension[high]) AND glucose[high]) AND bmi[normal]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                         stroke_risk[high] : 0.0\n",
      "\n",
      "RULE #69:\n",
      "  IF (((age[middle] AND hypertension[high]) AND glucose[high]) AND bmi[normal]) AND heart_disease[high] THEN stroke_risk[high]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[middle]                                            : 0.0\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[high]                                          : 0.6799999999999999\n",
      "  - bmi[normal]                                            : 0.0\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[middle] AND hypertension[high]) AND glucose[high]) AND bmi[normal]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                         stroke_risk[high] : 0.0\n",
      "\n",
      "RULE #70:\n",
      "  IF (((age[middle] AND hypertension[high]) AND glucose[high]) AND bmi[high]) AND heart_disease[low] THEN stroke_risk[high]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[middle]                                            : 0.0\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[high]                                          : 0.6799999999999999\n",
      "  - bmi[high]                                              : 0.08000000000000002\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[middle] AND hypertension[high]) AND glucose[high]) AND bmi[high]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                         stroke_risk[high] : 0.0\n",
      "\n",
      "RULE #71:\n",
      "  IF (((age[middle] AND hypertension[high]) AND glucose[high]) AND bmi[high]) AND heart_disease[high] THEN stroke_risk[high]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[middle]                                            : 0.0\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[high]                                          : 0.6799999999999999\n",
      "  - bmi[high]                                              : 0.08000000000000002\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[middle] AND hypertension[high]) AND glucose[high]) AND bmi[high]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                         stroke_risk[high] : 0.0\n",
      "\n",
      "RULE #72:\n",
      "  IF (((age[old] AND hypertension[low]) AND glucose[low]) AND bmi[low]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[old]                                               : 0.0\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[low]                                           : 0.0\n",
      "  - bmi[low]                                               : 0.0\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[old] AND hypertension[low]) AND glucose[low]) AND bmi[low]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #73:\n",
      "  IF (((age[old] AND hypertension[low]) AND glucose[low]) AND bmi[low]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[old]                                               : 0.0\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[low]                                           : 0.0\n",
      "  - bmi[low]                                               : 0.0\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[old] AND hypertension[low]) AND glucose[low]) AND bmi[low]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #74:\n",
      "  IF (((age[old] AND hypertension[low]) AND glucose[low]) AND bmi[normal]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[old]                                               : 0.0\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[low]                                           : 0.0\n",
      "  - bmi[normal]                                            : 0.0\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[old] AND hypertension[low]) AND glucose[low]) AND bmi[normal]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #75:\n",
      "  IF (((age[old] AND hypertension[low]) AND glucose[low]) AND bmi[normal]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[old]                                               : 0.0\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[low]                                           : 0.0\n",
      "  - bmi[normal]                                            : 0.0\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[old] AND hypertension[low]) AND glucose[low]) AND bmi[normal]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #76:\n",
      "  IF (((age[old] AND hypertension[low]) AND glucose[low]) AND bmi[high]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[old]                                               : 0.0\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[low]                                           : 0.0\n",
      "  - bmi[high]                                              : 0.08000000000000002\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[old] AND hypertension[low]) AND glucose[low]) AND bmi[high]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #77:\n",
      "  IF (((age[old] AND hypertension[low]) AND glucose[low]) AND bmi[high]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[old]                                               : 0.0\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[low]                                           : 0.0\n",
      "  - bmi[high]                                              : 0.08000000000000002\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[old] AND hypertension[low]) AND glucose[low]) AND bmi[high]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #78:\n",
      "  IF (((age[old] AND hypertension[low]) AND glucose[normal]) AND bmi[low]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[old]                                               : 0.0\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[normal]                                        : 0.0\n",
      "  - bmi[low]                                               : 0.0\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[old] AND hypertension[low]) AND glucose[normal]) AND bmi[low]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #79:\n",
      "  IF (((age[old] AND hypertension[low]) AND glucose[normal]) AND bmi[low]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[old]                                               : 0.0\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[normal]                                        : 0.0\n",
      "  - bmi[low]                                               : 0.0\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[old] AND hypertension[low]) AND glucose[normal]) AND bmi[low]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #80:\n",
      "  IF (((age[old] AND hypertension[low]) AND glucose[normal]) AND bmi[normal]) AND heart_disease[low] THEN stroke_risk[low]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[old]                                               : 0.0\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[normal]                                        : 0.0\n",
      "  - bmi[normal]                                            : 0.0\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[old] AND hypertension[low]) AND glucose[normal]) AND bmi[normal]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                          stroke_risk[low] : 0.0\n",
      "\n",
      "RULE #81:\n",
      "  IF (((age[old] AND hypertension[low]) AND glucose[normal]) AND bmi[normal]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[old]                                               : 0.0\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[normal]                                        : 0.0\n",
      "  - bmi[normal]                                            : 0.0\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[old] AND hypertension[low]) AND glucose[normal]) AND bmi[normal]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #82:\n",
      "  IF (((age[old] AND hypertension[low]) AND glucose[normal]) AND bmi[high]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[old]                                               : 0.0\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[normal]                                        : 0.0\n",
      "  - bmi[high]                                              : 0.08000000000000002\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[old] AND hypertension[low]) AND glucose[normal]) AND bmi[high]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #83:\n",
      "  IF (((age[old] AND hypertension[low]) AND glucose[normal]) AND bmi[high]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[old]                                               : 0.0\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[normal]                                        : 0.0\n",
      "  - bmi[high]                                              : 0.08000000000000002\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[old] AND hypertension[low]) AND glucose[normal]) AND bmi[high]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #84:\n",
      "  IF (((age[old] AND hypertension[low]) AND glucose[high]) AND bmi[low]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[old]                                               : 0.0\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[high]                                          : 0.6799999999999999\n",
      "  - bmi[low]                                               : 0.0\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[old] AND hypertension[low]) AND glucose[high]) AND bmi[low]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #85:\n",
      "  IF (((age[old] AND hypertension[low]) AND glucose[high]) AND bmi[low]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[old]                                               : 0.0\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[high]                                          : 0.6799999999999999\n",
      "  - bmi[low]                                               : 0.0\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[old] AND hypertension[low]) AND glucose[high]) AND bmi[low]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #86:\n",
      "  IF (((age[old] AND hypertension[low]) AND glucose[high]) AND bmi[normal]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[old]                                               : 0.0\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[high]                                          : 0.6799999999999999\n",
      "  - bmi[normal]                                            : 0.0\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[old] AND hypertension[low]) AND glucose[high]) AND bmi[normal]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #87:\n",
      "  IF (((age[old] AND hypertension[low]) AND glucose[high]) AND bmi[normal]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[old]                                               : 0.0\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[high]                                          : 0.6799999999999999\n",
      "  - bmi[normal]                                            : 0.0\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[old] AND hypertension[low]) AND glucose[high]) AND bmi[normal]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #88:\n",
      "  IF (((age[old] AND hypertension[low]) AND glucose[high]) AND bmi[high]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[old]                                               : 0.0\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[high]                                          : 0.6799999999999999\n",
      "  - bmi[high]                                              : 0.08000000000000002\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[old] AND hypertension[low]) AND glucose[high]) AND bmi[high]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #89:\n",
      "  IF (((age[old] AND hypertension[low]) AND glucose[high]) AND bmi[high]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[old]                                               : 0.0\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[high]                                          : 0.6799999999999999\n",
      "  - bmi[high]                                              : 0.08000000000000002\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[old] AND hypertension[low]) AND glucose[high]) AND bmi[high]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #90:\n",
      "  IF (((age[old] AND hypertension[high]) AND glucose[low]) AND bmi[low]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[old]                                               : 0.0\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[low]                                           : 0.0\n",
      "  - bmi[low]                                               : 0.0\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[old] AND hypertension[high]) AND glucose[low]) AND bmi[low]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #91:\n",
      "  IF (((age[old] AND hypertension[high]) AND glucose[low]) AND bmi[low]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[old]                                               : 0.0\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[low]                                           : 0.0\n",
      "  - bmi[low]                                               : 0.0\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[old] AND hypertension[high]) AND glucose[low]) AND bmi[low]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #92:\n",
      "  IF (((age[old] AND hypertension[high]) AND glucose[low]) AND bmi[normal]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[old]                                               : 0.0\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[low]                                           : 0.0\n",
      "  - bmi[normal]                                            : 0.0\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[old] AND hypertension[high]) AND glucose[low]) AND bmi[normal]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #93:\n",
      "  IF (((age[old] AND hypertension[high]) AND glucose[low]) AND bmi[normal]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[old]                                               : 0.0\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[low]                                           : 0.0\n",
      "  - bmi[normal]                                            : 0.0\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[old] AND hypertension[high]) AND glucose[low]) AND bmi[normal]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #94:\n",
      "  IF (((age[old] AND hypertension[high]) AND glucose[low]) AND bmi[high]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[old]                                               : 0.0\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[low]                                           : 0.0\n",
      "  - bmi[high]                                              : 0.08000000000000002\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[old] AND hypertension[high]) AND glucose[low]) AND bmi[high]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #95:\n",
      "  IF (((age[old] AND hypertension[high]) AND glucose[low]) AND bmi[high]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[old]                                               : 0.0\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[low]                                           : 0.0\n",
      "  - bmi[high]                                              : 0.08000000000000002\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[old] AND hypertension[high]) AND glucose[low]) AND bmi[high]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #96:\n",
      "  IF (((age[old] AND hypertension[high]) AND glucose[normal]) AND bmi[low]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[old]                                               : 0.0\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[normal]                                        : 0.0\n",
      "  - bmi[low]                                               : 0.0\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[old] AND hypertension[high]) AND glucose[normal]) AND bmi[low]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #97:\n",
      "  IF (((age[old] AND hypertension[high]) AND glucose[normal]) AND bmi[low]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[old]                                               : 0.0\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[normal]                                        : 0.0\n",
      "  - bmi[low]                                               : 0.0\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[old] AND hypertension[high]) AND glucose[normal]) AND bmi[low]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #98:\n",
      "  IF (((age[old] AND hypertension[high]) AND glucose[normal]) AND bmi[normal]) AND heart_disease[low] THEN stroke_risk[low]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[old]                                               : 0.0\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[normal]                                        : 0.0\n",
      "  - bmi[normal]                                            : 0.0\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[old] AND hypertension[high]) AND glucose[normal]) AND bmi[normal]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                          stroke_risk[low] : 0.0\n",
      "\n",
      "RULE #99:\n",
      "  IF (((age[old] AND hypertension[high]) AND glucose[normal]) AND bmi[normal]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[old]                                               : 0.0\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[normal]                                        : 0.0\n",
      "  - bmi[normal]                                            : 0.0\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[old] AND hypertension[high]) AND glucose[normal]) AND bmi[normal]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #100:\n",
      "  IF (((age[old] AND hypertension[high]) AND glucose[normal]) AND bmi[high]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[old]                                               : 0.0\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[normal]                                        : 0.0\n",
      "  - bmi[high]                                              : 0.08000000000000002\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[old] AND hypertension[high]) AND glucose[normal]) AND bmi[high]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #101:\n",
      "  IF (((age[old] AND hypertension[high]) AND glucose[normal]) AND bmi[high]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[old]                                               : 0.0\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[normal]                                        : 0.0\n",
      "  - bmi[high]                                              : 0.08000000000000002\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[old] AND hypertension[high]) AND glucose[normal]) AND bmi[high]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #102:\n",
      "  IF (((age[old] AND hypertension[high]) AND glucose[high]) AND bmi[low]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[old]                                               : 0.0\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[high]                                          : 0.6799999999999999\n",
      "  - bmi[low]                                               : 0.0\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[old] AND hypertension[high]) AND glucose[high]) AND bmi[low]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #103:\n",
      "  IF (((age[old] AND hypertension[high]) AND glucose[high]) AND bmi[low]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[old]                                               : 0.0\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[high]                                          : 0.6799999999999999\n",
      "  - bmi[low]                                               : 0.0\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[old] AND hypertension[high]) AND glucose[high]) AND bmi[low]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #104:\n",
      "  IF (((age[old] AND hypertension[high]) AND glucose[high]) AND bmi[normal]) AND heart_disease[low] THEN stroke_risk[high]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[old]                                               : 0.0\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[high]                                          : 0.6799999999999999\n",
      "  - bmi[normal]                                            : 0.0\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[old] AND hypertension[high]) AND glucose[high]) AND bmi[normal]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                         stroke_risk[high] : 0.0\n",
      "\n",
      "RULE #105:\n",
      "  IF (((age[old] AND hypertension[high]) AND glucose[high]) AND bmi[normal]) AND heart_disease[high] THEN stroke_risk[high]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[old]                                               : 0.0\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[high]                                          : 0.6799999999999999\n",
      "  - bmi[normal]                                            : 0.0\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[old] AND hypertension[high]) AND glucose[high]) AND bmi[normal]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                         stroke_risk[high] : 0.0\n",
      "\n",
      "RULE #106:\n",
      "  IF (((age[old] AND hypertension[high]) AND glucose[high]) AND bmi[high]) AND heart_disease[low] THEN stroke_risk[high]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[old]                                               : 0.0\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[high]                                          : 0.6799999999999999\n",
      "  - bmi[high]                                              : 0.08000000000000002\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[old] AND hypertension[high]) AND glucose[high]) AND bmi[high]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                         stroke_risk[high] : 0.0\n",
      "\n",
      "RULE #107:\n",
      "  IF (((age[old] AND hypertension[high]) AND glucose[high]) AND bmi[high]) AND heart_disease[high] THEN stroke_risk[high]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[old]                                               : 0.0\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[high]                                          : 0.6799999999999999\n",
      "  - bmi[high]                                              : 0.08000000000000002\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[old] AND hypertension[high]) AND glucose[high]) AND bmi[high]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                         stroke_risk[high] : 0.0\n",
      "\n",
      "RULE #108:\n",
      "  IF (((age[aged] AND hypertension[low]) AND glucose[low]) AND bmi[low]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[aged]                                              : 0.18\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[low]                                           : 0.0\n",
      "  - bmi[low]                                               : 0.0\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[aged] AND hypertension[low]) AND glucose[low]) AND bmi[low]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #109:\n",
      "  IF (((age[aged] AND hypertension[low]) AND glucose[low]) AND bmi[low]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[aged]                                              : 0.18\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[low]                                           : 0.0\n",
      "  - bmi[low]                                               : 0.0\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[aged] AND hypertension[low]) AND glucose[low]) AND bmi[low]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #110:\n",
      "  IF (((age[aged] AND hypertension[low]) AND glucose[low]) AND bmi[normal]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[aged]                                              : 0.18\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[low]                                           : 0.0\n",
      "  - bmi[normal]                                            : 0.0\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[aged] AND hypertension[low]) AND glucose[low]) AND bmi[normal]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #111:\n",
      "  IF (((age[aged] AND hypertension[low]) AND glucose[low]) AND bmi[normal]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[aged]                                              : 0.18\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[low]                                           : 0.0\n",
      "  - bmi[normal]                                            : 0.0\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[aged] AND hypertension[low]) AND glucose[low]) AND bmi[normal]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #112:\n",
      "  IF (((age[aged] AND hypertension[low]) AND glucose[low]) AND bmi[high]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[aged]                                              : 0.18\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[low]                                           : 0.0\n",
      "  - bmi[high]                                              : 0.08000000000000002\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[aged] AND hypertension[low]) AND glucose[low]) AND bmi[high]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #113:\n",
      "  IF (((age[aged] AND hypertension[low]) AND glucose[low]) AND bmi[high]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[aged]                                              : 0.18\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[low]                                           : 0.0\n",
      "  - bmi[high]                                              : 0.08000000000000002\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[aged] AND hypertension[low]) AND glucose[low]) AND bmi[high]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #114:\n",
      "  IF (((age[aged] AND hypertension[low]) AND glucose[normal]) AND bmi[low]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[aged]                                              : 0.18\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[normal]                                        : 0.0\n",
      "  - bmi[low]                                               : 0.0\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[aged] AND hypertension[low]) AND glucose[normal]) AND bmi[low]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #115:\n",
      "  IF (((age[aged] AND hypertension[low]) AND glucose[normal]) AND bmi[low]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[aged]                                              : 0.18\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[normal]                                        : 0.0\n",
      "  - bmi[low]                                               : 0.0\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[aged] AND hypertension[low]) AND glucose[normal]) AND bmi[low]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #116:\n",
      "  IF (((age[aged] AND hypertension[low]) AND glucose[normal]) AND bmi[normal]) AND heart_disease[low] THEN stroke_risk[low]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[aged]                                              : 0.18\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[normal]                                        : 0.0\n",
      "  - bmi[normal]                                            : 0.0\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[aged] AND hypertension[low]) AND glucose[normal]) AND bmi[normal]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                          stroke_risk[low] : 0.0\n",
      "\n",
      "RULE #117:\n",
      "  IF (((age[aged] AND hypertension[low]) AND glucose[normal]) AND bmi[normal]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[aged]                                              : 0.18\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[normal]                                        : 0.0\n",
      "  - bmi[normal]                                            : 0.0\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[aged] AND hypertension[low]) AND glucose[normal]) AND bmi[normal]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #118:\n",
      "  IF (((age[aged] AND hypertension[low]) AND glucose[normal]) AND bmi[high]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[aged]                                              : 0.18\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[normal]                                        : 0.0\n",
      "  - bmi[high]                                              : 0.08000000000000002\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[aged] AND hypertension[low]) AND glucose[normal]) AND bmi[high]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #119:\n",
      "  IF (((age[aged] AND hypertension[low]) AND glucose[normal]) AND bmi[high]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[aged]                                              : 0.18\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[normal]                                        : 0.0\n",
      "  - bmi[high]                                              : 0.08000000000000002\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[aged] AND hypertension[low]) AND glucose[normal]) AND bmi[high]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #120:\n",
      "  IF (((age[aged] AND hypertension[low]) AND glucose[high]) AND bmi[low]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[aged]                                              : 0.18\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[high]                                          : 0.6799999999999999\n",
      "  - bmi[low]                                               : 0.0\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[aged] AND hypertension[low]) AND glucose[high]) AND bmi[low]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #121:\n",
      "  IF (((age[aged] AND hypertension[low]) AND glucose[high]) AND bmi[low]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[aged]                                              : 0.18\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[high]                                          : 0.6799999999999999\n",
      "  - bmi[low]                                               : 0.0\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[aged] AND hypertension[low]) AND glucose[high]) AND bmi[low]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #122:\n",
      "  IF (((age[aged] AND hypertension[low]) AND glucose[high]) AND bmi[normal]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[aged]                                              : 0.18\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[high]                                          : 0.6799999999999999\n",
      "  - bmi[normal]                                            : 0.0\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[aged] AND hypertension[low]) AND glucose[high]) AND bmi[normal]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #123:\n",
      "  IF (((age[aged] AND hypertension[low]) AND glucose[high]) AND bmi[normal]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[aged]                                              : 0.18\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[high]                                          : 0.6799999999999999\n",
      "  - bmi[normal]                                            : 0.0\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[aged] AND hypertension[low]) AND glucose[high]) AND bmi[normal]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #124:\n",
      "  IF (((age[aged] AND hypertension[low]) AND glucose[high]) AND bmi[high]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[aged]                                              : 0.18\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[high]                                          : 0.6799999999999999\n",
      "  - bmi[high]                                              : 0.08000000000000002\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[aged] AND hypertension[low]) AND glucose[high]) AND bmi[high]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #125:\n",
      "  IF (((age[aged] AND hypertension[low]) AND glucose[high]) AND bmi[high]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[aged]                                              : 0.18\n",
      "  - hypertension[low]                                      : 0.0\n",
      "  - glucose[high]                                          : 0.6799999999999999\n",
      "  - bmi[high]                                              : 0.08000000000000002\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[aged] AND hypertension[low]) AND glucose[high]) AND bmi[high]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #126:\n",
      "  IF (((age[aged] AND hypertension[high]) AND glucose[low]) AND bmi[low]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[aged]                                              : 0.18\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[low]                                           : 0.0\n",
      "  - bmi[low]                                               : 0.0\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[aged] AND hypertension[high]) AND glucose[low]) AND bmi[low]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #127:\n",
      "  IF (((age[aged] AND hypertension[high]) AND glucose[low]) AND bmi[low]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[aged]                                              : 0.18\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[low]                                           : 0.0\n",
      "  - bmi[low]                                               : 0.0\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[aged] AND hypertension[high]) AND glucose[low]) AND bmi[low]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #128:\n",
      "  IF (((age[aged] AND hypertension[high]) AND glucose[low]) AND bmi[normal]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[aged]                                              : 0.18\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[low]                                           : 0.0\n",
      "  - bmi[normal]                                            : 0.0\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[aged] AND hypertension[high]) AND glucose[low]) AND bmi[normal]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #129:\n",
      "  IF (((age[aged] AND hypertension[high]) AND glucose[low]) AND bmi[normal]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[aged]                                              : 0.18\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[low]                                           : 0.0\n",
      "  - bmi[normal]                                            : 0.0\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[aged] AND hypertension[high]) AND glucose[low]) AND bmi[normal]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #130:\n",
      "  IF (((age[aged] AND hypertension[high]) AND glucose[low]) AND bmi[high]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[aged]                                              : 0.18\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[low]                                           : 0.0\n",
      "  - bmi[high]                                              : 0.08000000000000002\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[aged] AND hypertension[high]) AND glucose[low]) AND bmi[high]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #131:\n",
      "  IF (((age[aged] AND hypertension[high]) AND glucose[low]) AND bmi[high]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[aged]                                              : 0.18\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[low]                                           : 0.0\n",
      "  - bmi[high]                                              : 0.08000000000000002\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[aged] AND hypertension[high]) AND glucose[low]) AND bmi[high]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #132:\n",
      "  IF (((age[aged] AND hypertension[high]) AND glucose[normal]) AND bmi[low]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[aged]                                              : 0.18\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[normal]                                        : 0.0\n",
      "  - bmi[low]                                               : 0.0\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[aged] AND hypertension[high]) AND glucose[normal]) AND bmi[low]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #133:\n",
      "  IF (((age[aged] AND hypertension[high]) AND glucose[normal]) AND bmi[low]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[aged]                                              : 0.18\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[normal]                                        : 0.0\n",
      "  - bmi[low]                                               : 0.0\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[aged] AND hypertension[high]) AND glucose[normal]) AND bmi[low]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #134:\n",
      "  IF (((age[aged] AND hypertension[high]) AND glucose[normal]) AND bmi[normal]) AND heart_disease[low] THEN stroke_risk[low]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[aged]                                              : 0.18\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[normal]                                        : 0.0\n",
      "  - bmi[normal]                                            : 0.0\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[aged] AND hypertension[high]) AND glucose[normal]) AND bmi[normal]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                          stroke_risk[low] : 0.0\n",
      "\n",
      "RULE #135:\n",
      "  IF (((age[aged] AND hypertension[high]) AND glucose[normal]) AND bmi[normal]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[aged]                                              : 0.18\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[normal]                                        : 0.0\n",
      "  - bmi[normal]                                            : 0.0\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[aged] AND hypertension[high]) AND glucose[normal]) AND bmi[normal]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #136:\n",
      "  IF (((age[aged] AND hypertension[high]) AND glucose[normal]) AND bmi[high]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[aged]                                              : 0.18\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[normal]                                        : 0.0\n",
      "  - bmi[high]                                              : 0.08000000000000002\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[aged] AND hypertension[high]) AND glucose[normal]) AND bmi[high]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #137:\n",
      "  IF (((age[aged] AND hypertension[high]) AND glucose[normal]) AND bmi[high]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[aged]                                              : 0.18\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[normal]                                        : 0.0\n",
      "  - bmi[high]                                              : 0.08000000000000002\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[aged] AND hypertension[high]) AND glucose[normal]) AND bmi[high]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #138:\n",
      "  IF (((age[aged] AND hypertension[high]) AND glucose[high]) AND bmi[low]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[aged]                                              : 0.18\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[high]                                          : 0.6799999999999999\n",
      "  - bmi[low]                                               : 0.0\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[aged] AND hypertension[high]) AND glucose[high]) AND bmi[low]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #139:\n",
      "  IF (((age[aged] AND hypertension[high]) AND glucose[high]) AND bmi[low]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[aged]                                              : 0.18\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[high]                                          : 0.6799999999999999\n",
      "  - bmi[low]                                               : 0.0\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[aged] AND hypertension[high]) AND glucose[high]) AND bmi[low]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #140:\n",
      "  IF (((age[aged] AND hypertension[high]) AND glucose[high]) AND bmi[normal]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[aged]                                              : 0.18\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[high]                                          : 0.6799999999999999\n",
      "  - bmi[normal]                                            : 0.0\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[aged] AND hypertension[high]) AND glucose[high]) AND bmi[normal]) AND heart_disease[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #141:\n",
      "  IF (((age[aged] AND hypertension[high]) AND glucose[high]) AND bmi[normal]) AND heart_disease[high] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[aged]                                              : 0.18\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[high]                                          : 0.6799999999999999\n",
      "  - bmi[normal]                                            : 0.0\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[aged] AND hypertension[high]) AND glucose[high]) AND bmi[normal]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.0\n",
      "\n",
      "RULE #142:\n",
      "  IF (((age[aged] AND hypertension[high]) AND glucose[high]) AND bmi[high]) AND heart_disease[low] THEN stroke_risk[medium]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[aged]                                              : 0.18\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[high]                                          : 0.6799999999999999\n",
      "  - bmi[high]                                              : 0.08000000000000002\n",
      "  - heart_disease[low]                                     : 1.0\n",
      "    (((age[aged] AND hypertension[high]) AND glucose[high]) AND bmi[high]) AND heart_disease[low] = 0.08000000000000002\n",
      "  Activation (THEN-clause):\n",
      "                                       stroke_risk[medium] : 0.08000000000000002\n",
      "\n",
      "RULE #143:\n",
      "  IF (((age[aged] AND hypertension[high]) AND glucose[high]) AND bmi[high]) AND heart_disease[high] THEN stroke_risk[high]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - age[aged]                                              : 0.18\n",
      "  - hypertension[high]                                     : 1.0\n",
      "  - glucose[high]                                          : 0.6799999999999999\n",
      "  - bmi[high]                                              : 0.08000000000000002\n",
      "  - heart_disease[high]                                    : 0.0\n",
      "    (((age[aged] AND hypertension[high]) AND glucose[high]) AND bmi[high]) AND heart_disease[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                         stroke_risk[high] : 0.0\n",
      "\n",
      "\n",
      "==============================\n",
      " Intermediaries and Conquests \n",
      "==============================\n",
      "Consequent: stroke_risk              = 0.49999999999999994\n",
      "  low:\n",
      "    Accumulate using accumulation_max : 0.0\n",
      "  medium:\n",
      "    Accumulate using accumulation_max : 0.08000000000000002\n",
      "  high:\n",
      "    Accumulate using accumulation_max : 0.0\n",
      "\n",
      "0.49999999999999994\n"
     ]
    }
   ],
   "source": [
    "\n",
    "from pprint import pprint\n",
    "\n",
    "def fuzzy_pred(row):\n",
    "    stroke_simulation.input[\"age\"] = row[\"age\"]\n",
    "    stroke_simulation.input[\"glucose\"] = row[\"avg_glucose_level\"]\n",
    "    stroke_simulation.input[\"bmi\"] = row[\"bmi\"]\n",
    "    stroke_simulation.input[\"hypertension\"] = row[\"hypertension\"]\n",
    "    stroke_simulation.input[\"heart_disease\"] = row[\"heart_disease\"]\n",
    "\n",
    "\n",
    "    stroke_simulation.compute()\n",
    "    return stroke_simulation.output[\"stroke_risk\"]\n",
    "\n",
    "stroke_simulation.input[\"age\"] = 72\n",
    "stroke_simulation.input[\"glucose\"] = 220\n",
    "stroke_simulation.input[\"bmi\"] = 30\n",
    "stroke_simulation.input[\"hypertension\"] = 1\n",
    "stroke_simulation.input[\"heart_disease\"] = 0\n",
    "\n",
    "stroke_simulation.compute()\n",
    "stroke_simulation.print_state()\n",
    "stroke_predict = stroke_simulation.output[\"stroke_risk\"]\n",
    "print(stroke_predict)\n",
    "\n",
    "# result = data.copy()\n",
    "# result = result.sample(frac=0.01)\n",
    "# result[\"stroke_predicted\"] = result.apply(fuzzy_pred, axis=1)\n",
    "# # result[\"stroke_predicted\"] = result['stroke'].apply(lambda x: 1 if x> 0.5 else 0, axis=1)\n",
    "\n",
    "# print(result.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MAE: 0.4596\n",
      "MSE: 0.2265\n",
      "RMSE: 0.4760\n",
      "R² Score: -3.0918\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import mean_absolute_error, mean_squared_error, r2_score\n",
    "import numpy as np\n",
    "\n",
    "# Создаем копию данных и прогнозируем значения\n",
    "result = data.copy()\n",
    "result = result.sample(frac=0.01)  # Берем 1% данных для теста\n",
    "result[\"stroke_predicted\"] = result.apply(fuzzy_pred, axis=1)\n",
    "\n",
    "# Истинные и предсказанные значения\n",
    "y_true = result[\"stroke\"]\n",
    "y_pred = result[\"stroke_predicted\"]\n",
    "\n",
    "# Вычисляем метрики\n",
    "mae = mean_absolute_error(y_true, y_pred)\n",
    "mse = mean_squared_error(y_true, y_pred)\n",
    "rmse = np.sqrt(mse)\n",
    "r2 = r2_score(y_true, y_pred)\n",
    "\n",
    "# Выводим результаты\n",
    "print(f\"MAE: {mae:.4f}\") # ближе к 0 - лучше\n",
    "print(f\"MSE: {mse:.4f}\") # ближе к 0 - лучше\n",
    "print(f\"RMSE: {rmse:.4f}\") # тоже\n",
    "print(f\"R² Score: {r2:.4f}\") # а тут ближе к 1 - лучше"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### ну короче... противоречивые результаты, но в основном они говорят о том, что модель данная - такое себе. в чем я, собственно, не знаю, согласна или нет... по показателям людей здесь и правда мог бы быть инсульт, ведь риск его развития есть, а если вероятность его развития больше 0,2 вроде, то это высокая вероятность уже... короче сложно такие задачи решать с помощью нечетких переменных"
   ]
  }
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