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Add classification cardio task
2025-02-22 19:27:17 +04:00
{
"cells": [
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"|--- ap_hi <= 129.50\n",
"| |--- age <= 54.65\n",
"| | |--- cholesterol <= 2.50\n",
"| | | |--- age <= 43.79\n",
"| | | | |--- cholesterol <= 1.50\n",
"| | | | | |--- ap_hi <= 114.50\n",
"| | | | | | |--- class: 0\n",
"| | | | | |--- ap_hi > 114.50\n",
"| | | | | | |--- class: 0\n",
"| | | | |--- cholesterol > 1.50\n",
"| | | | | |--- bmi <= 28.87\n",
"| | | | | | |--- class: 0\n",
"| | | | | |--- bmi > 28.87\n",
"| | | | | | |--- class: 0\n",
"| | | |--- age > 43.79\n",
"| | | | |--- ap_hi <= 119.50\n",
"| | | | | |--- bmi <= 22.05\n",
"| | | | | | |--- class: 0\n",
"| | | | | |--- bmi > 22.05\n",
"| | | | | | |--- class: 0\n",
"| | | | |--- ap_hi > 119.50\n",
"| | | | | |--- bmi <= 27.71\n",
"| | | | | | |--- class: 0\n",
"| | | | | |--- bmi > 27.71\n",
"| | | | | | |--- class: 0\n",
"| | |--- cholesterol > 2.50\n",
"| | | |--- bmi <= 29.04\n",
"| | | | |--- age <= 41.60\n",
"| | | | | |--- ap_hi <= 115.00\n",
"| | | | | | |--- class: 0\n",
"| | | | | |--- ap_hi > 115.00\n",
"| | | | | | |--- class: 0\n",
"| | | | |--- age > 41.60\n",
"| | | | | |--- age <= 54.17\n",
"| | | | | | |--- class: 1\n",
"| | | | | |--- age > 54.17\n",
"| | | | | | |--- class: 0\n",
"| | | |--- bmi > 29.04\n",
"| | | | |--- age <= 54.01\n",
"| | | | | |--- age <= 39.75\n",
"| | | | | | |--- class: 0\n",
"| | | | | |--- age > 39.75\n",
"| | | | | | |--- class: 1\n",
"| | | | |--- age > 54.01\n",
"| | | | | |--- bmi <= 35.02\n",
"| | | | | | |--- class: 0\n",
"| | | | | |--- bmi > 35.02\n",
"| | | | | | |--- class: 1\n",
"| |--- age > 54.65\n",
"| | |--- cholesterol <= 2.50\n",
"| | | |--- age <= 60.71\n",
"| | | | |--- ap_hi <= 118.50\n",
"| | | | | |--- bmi <= 23.33\n",
"| | | | | | |--- class: 0\n",
"| | | | | |--- bmi > 23.33\n",
"| | | | | | |--- class: 0\n",
"| | | | |--- ap_hi > 118.50\n",
"| | | | | |--- bmi <= 32.89\n",
"| | | | | | |--- class: 0\n",
"| | | | | |--- bmi > 32.89\n",
"| | | | | | |--- class: 1\n",
"| | | |--- age > 60.71\n",
"| | | | |--- bmi <= 20.51\n",
"| | | | | |--- age <= 64.31\n",
"| | | | | | |--- class: 0\n",
"| | | | | |--- age > 64.31\n",
"| | | | | | |--- class: 1\n",
"| | | | |--- bmi > 20.51\n",
"| | | | | |--- ap_hi <= 115.50\n",
"| | | | | | |--- class: 0\n",
"| | | | | |--- ap_hi > 115.50\n",
"| | | | | | |--- class: 1\n",
"| | |--- cholesterol > 2.50\n",
"| | | |--- bmi <= 26.03\n",
"| | | | |--- age <= 60.89\n",
"| | | | | |--- age <= 60.48\n",
"| | | | | | |--- class: 1\n",
"| | | | | |--- age > 60.48\n",
"| | | | | | |--- class: 0\n",
"| | | | |--- age > 60.89\n",
"| | | | | |--- bmi <= 25.91\n",
"| | | | | | |--- class: 1\n",
"| | | | | |--- bmi > 25.91\n",
"| | | | | | |--- class: 0\n",
"| | | |--- bmi > 26.03\n",
"| | | | |--- age <= 59.39\n",
"| | | | | |--- bmi <= 35.93\n",
"| | | | | | |--- class: 1\n",
"| | | | | |--- bmi > 35.93\n",
"| | | | | | |--- class: 1\n",
"| | | | |--- age > 59.39\n",
"| | | | | |--- bmi <= 35.12\n",
"| | | | | | |--- class: 1\n",
"| | | | | |--- bmi > 35.12\n",
"| | | | | | |--- class: 1\n",
"|--- ap_hi > 129.50\n",
"| |--- ap_hi <= 138.50\n",
"| | |--- cholesterol <= 2.50\n",
"| | | |--- age <= 59.54\n",
"| | | | |--- bmi <= 21.64\n",
"| | | | | |--- bmi <= 17.30\n",
"| | | | | | |--- class: 1\n",
"| | | | | |--- bmi > 17.30\n",
"| | | | | | |--- class: 0\n",
"| | | | |--- bmi > 21.64\n",
"| | | | | |--- age <= 39.99\n",
"| | | | | | |--- class: 0\n",
"| | | | | |--- age > 39.99\n",
"| | | | | | |--- class: 1\n",
"| | | |--- age > 59.54\n",
"| | | | |--- age <= 62.46\n",
"| | | | | |--- bmi <= 20.61\n",
"| | | | | | |--- class: 0\n",
"| | | | | |--- bmi > 20.61\n",
"| | | | | | |--- class: 1\n",
"| | | | |--- age > 62.46\n",
"| | | | | |--- age <= 64.00\n",
"| | | | | | |--- class: 1\n",
"| | | | | |--- age > 64.00\n",
"| | | | | | |--- class: 1\n",
"| | |--- cholesterol > 2.50\n",
"| | | |--- bmi <= 30.74\n",
"| | | | |--- bmi <= 30.06\n",
"| | | | | |--- bmi <= 23.93\n",
"| | | | | | |--- class: 1\n",
"| | | | | |--- bmi > 23.93\n",
"| | | | | | |--- class: 1\n",
"| | | | |--- bmi > 30.06\n",
"| | | | | |--- bmi <= 30.69\n",
"| | | | | | |--- class: 1\n",
"| | | | | |--- bmi > 30.69\n",
"| | | | | | |--- class: 0\n",
"| | | |--- bmi > 30.74\n",
"| | | | |--- bmi <= 32.05\n",
"| | | | | |--- age <= 43.63\n",
"| | | | | | |--- class: 0\n",
"| | | | | |--- age > 43.63\n",
"| | | | | | |--- class: 1\n",
"| | | | |--- bmi > 32.05\n",
"| | | | | |--- bmi <= 32.34\n",
"| | | | | | |--- class: 1\n",
"| | | | | |--- bmi > 32.34\n",
"| | | | | | |--- class: 1\n",
"| |--- ap_hi > 138.50\n",
"| | |--- ap_hi <= 149.50\n",
"| | | |--- age <= 39.56\n",
"| | | | |--- bmi <= 38.19\n",
"| | | | | |--- age <= 39.54\n",
"| | | | | | |--- class: 1\n",
"| | | | | |--- age > 39.54\n",
"| | | | | | |--- class: 0\n",
"| | | | |--- bmi > 38.19\n",
"| | | | | |--- bmi <= 50.55\n",
"| | | | | | |--- class: 0\n",
"| | | | | |--- bmi > 50.55\n",
"| | | | | | |--- class: 1\n",
"| | | |--- age > 39.56\n",
"| | | | |--- age <= 47.57\n",
"| | | | | |--- bmi <= 19.23\n",
"| | | | | | |--- class: 0\n",
"| | | | | |--- bmi > 19.23\n",
"| | | | | | |--- class: 1\n",
"| | | | |--- age > 47.57\n",
"| | | | | |--- age <= 61.57\n",
"| | | | | | |--- class: 1\n",
"| | | | | |--- age > 61.57\n",
"| | | | | | |--- class: 1\n",
"| | |--- ap_hi > 149.50\n",
"| | | |--- bmi <= 20.48\n",
"| | | | |--- age <= 64.27\n",
"| | | | | |--- age <= 55.82\n",
"| | | | | | |--- class: 1\n",
"| | | | | |--- age > 55.82\n",
"| | | | | | |--- class: 1\n",
"| | | | |--- age > 64.27\n",
"| | | | | |--- class: 0\n",
"| | | |--- bmi > 20.48\n",
"| | | | |--- age <= 64.35\n",
"| | | | | |--- age <= 49.82\n",
"| | | | | | |--- class: 1\n",
"| | | | | |--- age > 49.82\n",
"| | | | | | |--- class: 1\n",
"| | | | |--- age > 64.35\n",
"| | | | | |--- bmi <= 36.80\n",
"| | | | | | |--- class: 1\n",
"| | | | | |--- bmi > 36.80\n",
"| | | | | | |--- class: 0\n",
"\n"
]
}
],
"source": [
"import pickle\n",
"import pandas as pd\n",
"from sklearn import tree\n",
"\n",
"df = pd.read_csv(\"data-cardio/cardio_clear.csv\", index_col=\"id\")\n",
"model = pickle.load(open(\"data-cardio//cardio.model.sav\", \"rb\"))\n",
"features = (\n",
" df\n",
" .drop([\"cardio\"], axis=1)\n",
" .columns.values.tolist()\n",
")\n",
"\n",
"rules = tree.export_text(model, feature_names=features)\n",
"print(rules)"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"63"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"[if (ap_hi <= 129.5) and (age <= 54.65) and (cholesterol <= 2.5) and (age <= 43.792) and (cholesterol <= 1.5) and (ap_hi <= 114.5) -> 0,\n",
" if (ap_hi <= 129.5) and (age <= 54.65) and (cholesterol <= 2.5) and (age <= 43.792) and (cholesterol <= 1.5) and (ap_hi > 114.5) -> 0,\n",
" if (ap_hi <= 129.5) and (age <= 54.65) and (cholesterol <= 2.5) and (age <= 43.792) and (cholesterol > 1.5) and (bmi <= 28.874) -> 0,\n",
" if (ap_hi <= 129.5) and (age <= 54.65) and (cholesterol <= 2.5) and (age <= 43.792) and (cholesterol > 1.5) and (bmi > 28.874) -> 0,\n",
" if (ap_hi <= 129.5) and (age <= 54.65) and (cholesterol <= 2.5) and (age > 43.792) and (ap_hi <= 119.5) and (bmi <= 22.045) -> 0,\n",
" if (ap_hi <= 129.5) and (age <= 54.65) and (cholesterol <= 2.5) and (age > 43.792) and (ap_hi <= 119.5) and (bmi > 22.045) -> 0,\n",
" if (ap_hi <= 129.5) and (age <= 54.65) and (cholesterol <= 2.5) and (age > 43.792) and (ap_hi > 119.5) and (bmi <= 27.71) -> 0,\n",
" if (ap_hi <= 129.5) and (age <= 54.65) and (cholesterol <= 2.5) and (age > 43.792) and (ap_hi > 119.5) and (bmi > 27.71) -> 0,\n",
" if (ap_hi <= 129.5) and (age <= 54.65) and (cholesterol > 2.5) and (bmi <= 29.043) and (age <= 41.599) and (ap_hi <= 115.0) -> 0,\n",
" if (ap_hi <= 129.5) and (age <= 54.65) and (cholesterol > 2.5) and (bmi <= 29.043) and (age <= 41.599) and (ap_hi > 115.0) -> 0,\n",
" if (ap_hi <= 129.5) and (age <= 54.65) and (cholesterol > 2.5) and (bmi <= 29.043) and (age > 41.599) and (age <= 54.167) -> 1,\n",
" if (ap_hi <= 129.5) and (age <= 54.65) and (cholesterol > 2.5) and (bmi <= 29.043) and (age > 41.599) and (age > 54.167) -> 0,\n",
" if (ap_hi <= 129.5) and (age <= 54.65) and (cholesterol > 2.5) and (bmi > 29.043) and (age <= 54.008) and (age <= 39.751) -> 0,\n",
" if (ap_hi <= 129.5) and (age <= 54.65) and (cholesterol > 2.5) and (bmi > 29.043) and (age <= 54.008) and (age > 39.751) -> 1,\n",
" if (ap_hi <= 129.5) and (age <= 54.65) and (cholesterol > 2.5) and (bmi > 29.043) and (age > 54.008) and (bmi <= 35.021) -> 0,\n",
" if (ap_hi <= 129.5) and (age <= 54.65) and (cholesterol > 2.5) and (bmi > 29.043) and (age > 54.008) and (bmi > 35.021) -> 1,\n",
" if (ap_hi <= 129.5) and (age > 54.65) and (cholesterol <= 2.5) and (age <= 60.707) and (ap_hi <= 118.5) and (bmi <= 23.329) -> 0,\n",
" if (ap_hi <= 129.5) and (age > 54.65) and (cholesterol <= 2.5) and (age <= 60.707) and (ap_hi <= 118.5) and (bmi > 23.329) -> 0,\n",
" if (ap_hi <= 129.5) and (age > 54.65) and (cholesterol <= 2.5) and (age <= 60.707) and (ap_hi > 118.5) and (bmi <= 32.886) -> 0,\n",
" if (ap_hi <= 129.5) and (age > 54.65) and (cholesterol <= 2.5) and (age <= 60.707) and (ap_hi > 118.5) and (bmi > 32.886) -> 1,\n",
" if (ap_hi <= 129.5) and (age > 54.65) and (cholesterol <= 2.5) and (age > 60.707) and (bmi <= 20.512) and (age <= 64.308) -> 0,\n",
" if (ap_hi <= 129.5) and (age > 54.65) and (cholesterol <= 2.5) and (age > 60.707) and (bmi <= 20.512) and (age > 64.308) -> 1,\n",
" if (ap_hi <= 129.5) and (age > 54.65) and (cholesterol <= 2.5) and (age > 60.707) and (bmi > 20.512) and (ap_hi <= 115.5) -> 0,\n",
" if (ap_hi <= 129.5) and (age > 54.65) and (cholesterol <= 2.5) and (age > 60.707) and (bmi > 20.512) and (ap_hi > 115.5) -> 1,\n",
" if (ap_hi <= 129.5) and (age > 54.65) and (cholesterol > 2.5) and (bmi <= 26.032) and (age <= 60.891) and (age <= 60.479) -> 1,\n",
" if (ap_hi <= 129.5) and (age > 54.65) and (cholesterol > 2.5) and (bmi <= 26.032) and (age <= 60.891) and (age > 60.479) -> 0,\n",
" if (ap_hi <= 129.5) and (age > 54.65) and (cholesterol > 2.5) and (bmi <= 26.032) and (age > 60.891) and (bmi <= 25.912) -> 1,\n",
" if (ap_hi <= 129.5) and (age > 54.65) and (cholesterol > 2.5) and (bmi <= 26.032) and (age > 60.891) and (bmi > 25.912) -> 0,\n",
" if (ap_hi <= 129.5) and (age > 54.65) and (cholesterol > 2.5) and (bmi > 26.032) and (age <= 59.39) and (bmi <= 35.932) -> 1,\n",
" if (ap_hi <= 129.5) and (age > 54.65) and (cholesterol > 2.5) and (bmi > 26.032) and (age <= 59.39) and (bmi > 35.932) -> 1,\n",
" if (ap_hi <= 129.5) and (age > 54.65) and (cholesterol > 2.5) and (bmi > 26.032) and (age > 59.39) and (bmi <= 35.121) -> 1,\n",
" if (ap_hi <= 129.5) and (age > 54.65) and (cholesterol > 2.5) and (bmi > 26.032) and (age > 59.39) and (bmi > 35.121) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol <= 2.5) and (age <= 59.536) and (bmi <= 21.637) and (bmi <= 17.3) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol <= 2.5) and (age <= 59.536) and (bmi <= 21.637) and (bmi > 17.3) -> 0,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol <= 2.5) and (age <= 59.536) and (bmi > 21.637) and (age <= 39.989) -> 0,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol <= 2.5) and (age <= 59.536) and (bmi > 21.637) and (age > 39.989) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol <= 2.5) and (age > 59.536) and (age <= 62.463) and (bmi <= 20.614) -> 0,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol <= 2.5) and (age > 59.536) and (age <= 62.463) and (bmi > 20.614) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol <= 2.5) and (age > 59.536) and (age > 62.463) and (age <= 63.998) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol <= 2.5) and (age > 59.536) and (age > 62.463) and (age > 63.998) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol > 2.5) and (bmi <= 30.744) and (bmi <= 30.056) and (bmi <= 23.927) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol > 2.5) and (bmi <= 30.744) and (bmi <= 30.056) and (bmi > 23.927) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol > 2.5) and (bmi <= 30.744) and (bmi > 30.056) and (bmi <= 30.69) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol > 2.5) and (bmi <= 30.744) and (bmi > 30.056) and (bmi > 30.69) -> 0,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol > 2.5) and (bmi > 30.744) and (bmi <= 32.049) and (age <= 43.632) -> 0,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol > 2.5) and (bmi > 30.744) and (bmi <= 32.049) and (age > 43.632) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol > 2.5) and (bmi > 30.744) and (bmi > 32.049) and (bmi <= 32.337) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol > 2.5) and (bmi > 30.744) and (bmi > 32.049) and (bmi > 32.337) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi > 138.5) and (ap_hi <= 149.5) and (age <= 39.558) and (bmi <= 38.186) and (age <= 39.538) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi > 138.5) and (ap_hi <= 149.5) and (age <= 39.558) and (bmi <= 38.186) and (age > 39.538) -> 0,\n",
" if (ap_hi > 129.5) and (ap_hi > 138.5) and (ap_hi <= 149.5) and (age <= 39.558) and (bmi > 38.186) and (bmi <= 50.547) -> 0,\n",
" if (ap_hi > 129.5) and (ap_hi > 138.5) and (ap_hi <= 149.5) and (age <= 39.558) and (bmi > 38.186) and (bmi > 50.547) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi > 138.5) and (ap_hi <= 149.5) and (age > 39.558) and (age <= 47.569) and (bmi <= 19.231) -> 0,\n",
" if (ap_hi > 129.5) and (ap_hi > 138.5) and (ap_hi <= 149.5) and (age > 39.558) and (age <= 47.569) and (bmi > 19.231) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi > 138.5) and (ap_hi <= 149.5) and (age > 39.558) and (age > 47.569) and (age <= 61.572) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi > 138.5) and (ap_hi <= 149.5) and (age > 39.558) and (age > 47.569) and (age > 61.572) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi > 138.5) and (ap_hi > 149.5) and (bmi <= 20.482) and (age <= 64.269) and (age <= 55.817) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi > 138.5) and (ap_hi > 149.5) and (bmi <= 20.482) and (age <= 64.269) and (age > 55.817) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi > 138.5) and (ap_hi > 149.5) and (bmi <= 20.482) and (age > 64.269) -> 0,\n",
" if (ap_hi > 129.5) and (ap_hi > 138.5) and (ap_hi > 149.5) and (bmi > 20.482) and (age <= 64.351) and (age <= 49.818) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi > 138.5) and (ap_hi > 149.5) and (bmi > 20.482) and (age <= 64.351) and (age > 49.818) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi > 138.5) and (ap_hi > 149.5) and (bmi > 20.482) and (age > 64.351) and (bmi <= 36.796) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi > 138.5) and (ap_hi > 149.5) and (bmi > 20.482) and (age > 64.351) and (bmi > 36.796) -> 0]"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from src.rules import get_rules\n",
"\n",
"\n",
"rules = get_rules(model, features, [0, 1])\n",
"display(len(rules))\n",
"rules"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"63"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"[if (ap_hi <= 129.5) and (age <= 54.65) and (cholesterol <= 2.5) -> 0,\n",
" if (ap_hi <= 129.5) and (ap_hi > 114.5) and (age <= 54.65) and (cholesterol <= 2.5) -> 0,\n",
" if (ap_hi <= 129.5) and (age <= 54.65) and (cholesterol <= 2.5) and (cholesterol > 1.5) and (bmi <= 28.874) -> 0,\n",
" if (ap_hi <= 129.5) and (age <= 54.65) and (cholesterol <= 2.5) and (cholesterol > 1.5) and (bmi > 28.874) -> 0,\n",
" if (ap_hi <= 129.5) and (age <= 54.65) and (age > 43.792) and (cholesterol <= 2.5) and (bmi <= 22.045) -> 0,\n",
" if (ap_hi <= 129.5) and (age <= 54.65) and (age > 43.792) and (cholesterol <= 2.5) and (bmi > 22.045) -> 0,\n",
" if (ap_hi <= 129.5) and (ap_hi > 119.5) and (age <= 54.65) and (age > 43.792) and (cholesterol <= 2.5) and (bmi <= 27.71) -> 0,\n",
" if (ap_hi <= 129.5) and (ap_hi > 119.5) and (age <= 54.65) and (age > 43.792) and (cholesterol <= 2.5) and (bmi > 27.71) -> 0,\n",
" if (ap_hi <= 129.5) and (age <= 54.65) and (cholesterol > 2.5) and (bmi <= 29.043) -> 0,\n",
" if (ap_hi <= 129.5) and (ap_hi > 115.0) and (age <= 54.65) and (cholesterol > 2.5) and (bmi <= 29.043) -> 0,\n",
" if (ap_hi <= 129.5) and (age <= 54.65) and (age > 41.599) and (cholesterol > 2.5) and (bmi <= 29.043) -> 1,\n",
" if (ap_hi <= 129.5) and (age <= 54.65) and (age > 41.599) and (cholesterol > 2.5) and (bmi <= 29.043) -> 0,\n",
" if (ap_hi <= 129.5) and (age <= 54.65) and (cholesterol > 2.5) and (bmi > 29.043) -> 0,\n",
" if (ap_hi <= 129.5) and (age <= 54.65) and (age > 39.751) and (cholesterol > 2.5) and (bmi > 29.043) -> 1,\n",
" if (ap_hi <= 129.5) and (age <= 54.65) and (age > 54.008) and (cholesterol > 2.5) and (bmi > 29.043) and (bmi <= 35.021) -> 0,\n",
" if (ap_hi <= 129.5) and (age <= 54.65) and (age > 54.008) and (cholesterol > 2.5) and (bmi > 29.043) -> 1,\n",
" if (ap_hi <= 129.5) and (age > 54.65) and (age <= 60.707) and (cholesterol <= 2.5) and (bmi <= 23.329) -> 0,\n",
" if (ap_hi <= 129.5) and (age > 54.65) and (age <= 60.707) and (cholesterol <= 2.5) and (bmi > 23.329) -> 0,\n",
" if (ap_hi <= 129.5) and (ap_hi > 118.5) and (age > 54.65) and (age <= 60.707) and (cholesterol <= 2.5) and (bmi <= 32.886) -> 0,\n",
" if (ap_hi <= 129.5) and (ap_hi > 118.5) and (age > 54.65) and (age <= 60.707) and (cholesterol <= 2.5) and (bmi > 32.886) -> 1,\n",
" if (ap_hi <= 129.5) and (age > 54.65) and (age <= 64.308) and (cholesterol <= 2.5) and (bmi <= 20.512) -> 0,\n",
" if (ap_hi <= 129.5) and (age > 54.65) and (cholesterol <= 2.5) and (bmi <= 20.512) -> 1,\n",
" if (ap_hi <= 129.5) and (age > 54.65) and (cholesterol <= 2.5) and (bmi > 20.512) -> 0,\n",
" if (ap_hi <= 129.5) and (ap_hi > 115.5) and (age > 54.65) and (cholesterol <= 2.5) and (bmi > 20.512) -> 1,\n",
" if (ap_hi <= 129.5) and (age > 54.65) and (age <= 60.891) and (cholesterol > 2.5) and (bmi <= 26.032) -> 1,\n",
" if (ap_hi <= 129.5) and (age > 54.65) and (age <= 60.891) and (cholesterol > 2.5) and (bmi <= 26.032) -> 0,\n",
" if (ap_hi <= 129.5) and (age > 54.65) and (cholesterol > 2.5) and (bmi <= 26.032) -> 1,\n",
" if (ap_hi <= 129.5) and (age > 54.65) and (cholesterol > 2.5) and (bmi <= 26.032) and (bmi > 25.912) -> 0,\n",
" if (ap_hi <= 129.5) and (age > 54.65) and (age <= 59.39) and (cholesterol > 2.5) and (bmi > 26.032) and (bmi <= 35.932) -> 1,\n",
" if (ap_hi <= 129.5) and (age > 54.65) and (age <= 59.39) and (cholesterol > 2.5) and (bmi > 26.032) -> 1,\n",
" if (ap_hi <= 129.5) and (age > 54.65) and (cholesterol > 2.5) and (bmi > 26.032) and (bmi <= 35.121) -> 1,\n",
" if (ap_hi <= 129.5) and (age > 54.65) and (cholesterol > 2.5) and (bmi > 26.032) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol <= 2.5) and (age <= 59.536) and (bmi <= 21.637) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol <= 2.5) and (age <= 59.536) and (bmi <= 21.637) and (bmi > 17.3) -> 0,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol <= 2.5) and (age <= 59.536) and (bmi > 21.637) -> 0,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol <= 2.5) and (age <= 59.536) and (age > 39.989) and (bmi > 21.637) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol <= 2.5) and (age > 59.536) and (age <= 62.463) and (bmi <= 20.614) -> 0,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol <= 2.5) and (age > 59.536) and (age <= 62.463) and (bmi > 20.614) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol <= 2.5) and (age > 59.536) and (age <= 63.998) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol <= 2.5) and (age > 59.536) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol > 2.5) and (bmi <= 30.744) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol > 2.5) and (bmi <= 30.744) and (bmi > 23.927) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol > 2.5) and (bmi <= 30.744) and (bmi > 30.056) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol > 2.5) and (bmi <= 30.744) and (bmi > 30.056) -> 0,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol > 2.5) and (bmi > 30.744) and (bmi <= 32.049) and (age <= 43.632) -> 0,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol > 2.5) and (bmi > 30.744) and (bmi <= 32.049) and (age > 43.632) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol > 2.5) and (bmi > 30.744) and (bmi <= 32.337) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol > 2.5) and (bmi > 30.744) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi <= 149.5) and (age <= 39.558) and (bmi <= 38.186) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi <= 149.5) and (age <= 39.558) and (age > 39.538) and (bmi <= 38.186) -> 0,\n",
" if (ap_hi > 129.5) and (ap_hi <= 149.5) and (age <= 39.558) and (bmi > 38.186) and (bmi <= 50.547) -> 0,\n",
" if (ap_hi > 129.5) and (ap_hi <= 149.5) and (age <= 39.558) and (bmi > 38.186) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi <= 149.5) and (age > 39.558) and (age <= 47.569) and (bmi <= 19.231) -> 0,\n",
" if (ap_hi > 129.5) and (ap_hi <= 149.5) and (age > 39.558) and (age <= 47.569) and (bmi > 19.231) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi <= 149.5) and (age > 39.558) and (age <= 61.572) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi <= 149.5) and (age > 39.558) -> 1,\n",
" if (ap_hi > 129.5) and (bmi <= 20.482) and (age <= 64.269) -> 1,\n",
" if (ap_hi > 129.5) and (bmi <= 20.482) and (age <= 64.269) and (age > 55.817) -> 1,\n",
" if (ap_hi > 129.5) and (bmi <= 20.482) and (age > 64.269) -> 0,\n",
" if (ap_hi > 129.5) and (bmi > 20.482) and (age <= 64.351) -> 1,\n",
" if (ap_hi > 129.5) and (bmi > 20.482) and (age <= 64.351) and (age > 49.818) -> 1,\n",
" if (ap_hi > 129.5) and (bmi > 20.482) and (bmi <= 36.796) and (age > 64.351) -> 1,\n",
" if (ap_hi > 129.5) and (bmi > 20.482) and (age > 64.351) -> 0]"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from src.rules import normalise_rules\n",
"\n",
"\n",
"rules = normalise_rules(rules)\n",
"display(len(rules))\n",
"rules"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"60"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"[if (ap_hi <= 129.5) and (age <= 54.65) and (cholesterol <= 2.5) -> 0,\n",
" if (ap_hi <= 129.5) and (ap_hi > 114.5) and (age <= 54.65) and (cholesterol <= 2.5) -> 0,\n",
" if (ap_hi <= 129.5) and (age <= 54.65) and (cholesterol <= 2.5) and (cholesterol > 1.5) and (bmi <= 28.874) -> 0,\n",
" if (ap_hi <= 129.5) and (age <= 54.65) and (cholesterol <= 2.5) and (cholesterol > 1.5) and (bmi > 28.874) -> 0,\n",
" if (ap_hi <= 129.5) and (age <= 54.65) and (age > 43.792) and (cholesterol <= 2.5) and (bmi <= 22.045) -> 0,\n",
" if (ap_hi <= 129.5) and (age <= 54.65) and (age > 43.792) and (cholesterol <= 2.5) and (bmi > 22.045) -> 0,\n",
" if (ap_hi <= 129.5) and (ap_hi > 119.5) and (age <= 54.65) and (age > 43.792) and (cholesterol <= 2.5) and (bmi <= 27.71) -> 0,\n",
" if (ap_hi <= 129.5) and (ap_hi > 119.5) and (age <= 54.65) and (age > 43.792) and (cholesterol <= 2.5) and (bmi > 27.71) -> 0,\n",
" if (ap_hi <= 129.5) and (age <= 54.65) and (cholesterol > 2.5) and (bmi <= 29.043) -> 0,\n",
" if (ap_hi <= 129.5) and (ap_hi > 115.0) and (age <= 54.65) and (cholesterol > 2.5) and (bmi <= 29.043) -> 0,\n",
" if (ap_hi <= 129.5) and (age <= 54.65) and (age > 41.599) and (cholesterol > 2.5) and (bmi <= 29.043) -> 0.5,\n",
" if (ap_hi <= 129.5) and (age <= 54.65) and (cholesterol > 2.5) and (bmi > 29.043) -> 0,\n",
" if (ap_hi <= 129.5) and (age <= 54.65) and (age > 39.751) and (cholesterol > 2.5) and (bmi > 29.043) -> 1,\n",
" if (ap_hi <= 129.5) and (age <= 54.65) and (age > 54.008) and (cholesterol > 2.5) and (bmi > 29.043) and (bmi <= 35.021) -> 0,\n",
" if (ap_hi <= 129.5) and (age <= 54.65) and (age > 54.008) and (cholesterol > 2.5) and (bmi > 29.043) -> 1,\n",
" if (ap_hi <= 129.5) and (age > 54.65) and (age <= 60.707) and (cholesterol <= 2.5) and (bmi <= 23.329) -> 0,\n",
" if (ap_hi <= 129.5) and (age > 54.65) and (age <= 60.707) and (cholesterol <= 2.5) and (bmi > 23.329) -> 0,\n",
" if (ap_hi <= 129.5) and (ap_hi > 118.5) and (age > 54.65) and (age <= 60.707) and (cholesterol <= 2.5) and (bmi <= 32.886) -> 0,\n",
" if (ap_hi <= 129.5) and (ap_hi > 118.5) and (age > 54.65) and (age <= 60.707) and (cholesterol <= 2.5) and (bmi > 32.886) -> 1,\n",
" if (ap_hi <= 129.5) and (age > 54.65) and (age <= 64.308) and (cholesterol <= 2.5) and (bmi <= 20.512) -> 0,\n",
" if (ap_hi <= 129.5) and (age > 54.65) and (cholesterol <= 2.5) and (bmi <= 20.512) -> 1,\n",
" if (ap_hi <= 129.5) and (age > 54.65) and (cholesterol <= 2.5) and (bmi > 20.512) -> 0,\n",
" if (ap_hi <= 129.5) and (ap_hi > 115.5) and (age > 54.65) and (cholesterol <= 2.5) and (bmi > 20.512) -> 1,\n",
" if (ap_hi <= 129.5) and (age > 54.65) and (age <= 60.891) and (cholesterol > 2.5) and (bmi <= 26.032) -> 0.5,\n",
" if (ap_hi <= 129.5) and (age > 54.65) and (cholesterol > 2.5) and (bmi <= 26.032) -> 1,\n",
" if (ap_hi <= 129.5) and (age > 54.65) and (cholesterol > 2.5) and (bmi <= 26.032) and (bmi > 25.912) -> 0,\n",
" if (ap_hi <= 129.5) and (age > 54.65) and (age <= 59.39) and (cholesterol > 2.5) and (bmi > 26.032) and (bmi <= 35.932) -> 1,\n",
" if (ap_hi <= 129.5) and (age > 54.65) and (age <= 59.39) and (cholesterol > 2.5) and (bmi > 26.032) -> 1,\n",
" if (ap_hi <= 129.5) and (age > 54.65) and (cholesterol > 2.5) and (bmi > 26.032) and (bmi <= 35.121) -> 1,\n",
" if (ap_hi <= 129.5) and (age > 54.65) and (cholesterol > 2.5) and (bmi > 26.032) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol <= 2.5) and (age <= 59.536) and (bmi <= 21.637) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol <= 2.5) and (age <= 59.536) and (bmi <= 21.637) and (bmi > 17.3) -> 0,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol <= 2.5) and (age <= 59.536) and (bmi > 21.637) -> 0,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol <= 2.5) and (age <= 59.536) and (age > 39.989) and (bmi > 21.637) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol <= 2.5) and (age > 59.536) and (age <= 62.463) and (bmi <= 20.614) -> 0,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol <= 2.5) and (age > 59.536) and (age <= 62.463) and (bmi > 20.614) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol <= 2.5) and (age > 59.536) and (age <= 63.998) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol <= 2.5) and (age > 59.536) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol > 2.5) and (bmi <= 30.744) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol > 2.5) and (bmi <= 30.744) and (bmi > 23.927) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol > 2.5) and (bmi <= 30.744) and (bmi > 30.056) -> 0.5,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol > 2.5) and (bmi > 30.744) and (bmi <= 32.049) and (age <= 43.632) -> 0,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol > 2.5) and (bmi > 30.744) and (bmi <= 32.049) and (age > 43.632) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol > 2.5) and (bmi > 30.744) and (bmi <= 32.337) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol > 2.5) and (bmi > 30.744) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi <= 149.5) and (age <= 39.558) and (bmi <= 38.186) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi <= 149.5) and (age <= 39.558) and (age > 39.538) and (bmi <= 38.186) -> 0,\n",
" if (ap_hi > 129.5) and (ap_hi <= 149.5) and (age <= 39.558) and (bmi > 38.186) and (bmi <= 50.547) -> 0,\n",
" if (ap_hi > 129.5) and (ap_hi <= 149.5) and (age <= 39.558) and (bmi > 38.186) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi <= 149.5) and (age > 39.558) and (age <= 47.569) and (bmi <= 19.231) -> 0,\n",
" if (ap_hi > 129.5) and (ap_hi <= 149.5) and (age > 39.558) and (age <= 47.569) and (bmi > 19.231) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi <= 149.5) and (age > 39.558) and (age <= 61.572) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi <= 149.5) and (age > 39.558) -> 1,\n",
" if (ap_hi > 129.5) and (bmi <= 20.482) and (age <= 64.269) -> 1,\n",
" if (ap_hi > 129.5) and (bmi <= 20.482) and (age <= 64.269) and (age > 55.817) -> 1,\n",
" if (ap_hi > 129.5) and (bmi <= 20.482) and (age > 64.269) -> 0,\n",
" if (ap_hi > 129.5) and (bmi > 20.482) and (age <= 64.351) -> 1,\n",
" if (ap_hi > 129.5) and (bmi > 20.482) and (age <= 64.351) and (age > 49.818) -> 1,\n",
" if (ap_hi > 129.5) and (bmi > 20.482) and (bmi <= 36.796) and (age > 64.351) -> 1,\n",
" if (ap_hi > 129.5) and (bmi > 20.482) and (age > 64.351) -> 0]"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from src.rules import delete_same_rules\n",
"\n",
"\n",
"rules = delete_same_rules(rules)\n",
"display(len(rules))\n",
"rules"
]
},
{
"cell_type": "code",
"execution_count": 102,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"57"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"[if (ap_hi <= 129.5) and (age <= 54.65) and (cholesterol <= 2.5) -> 0,\n",
" if (ap_hi <= 129.5) and (ap_hi > 114.5) and (age <= 54.65) and (cholesterol <= 2.5) -> 0,\n",
" if (ap_hi <= 129.5) and (age <= 54.65) and (cholesterol <= 2.5) and (cholesterol > 1.5) and (bmi <= 28.874) -> 0,\n",
" if (ap_hi <= 129.5) and (age <= 54.65) and (cholesterol <= 2.5) and (cholesterol > 1.5) and (bmi > 28.874) -> 0,\n",
" if (ap_hi <= 129.5) and (age <= 54.65) and (age > 43.792) and (cholesterol <= 2.5) and (bmi <= 22.045) -> 0,\n",
" if (ap_hi <= 129.5) and (age <= 54.65) and (age > 43.792) and (cholesterol <= 2.5) and (bmi > 22.045) -> 0,\n",
" if (ap_hi <= 129.5) and (ap_hi > 119.5) and (age <= 54.65) and (age > 43.792) and (cholesterol <= 2.5) and (bmi <= 27.71) -> 0,\n",
" if (ap_hi <= 129.5) and (ap_hi > 119.5) and (age <= 54.65) and (age > 43.792) and (cholesterol <= 2.5) and (bmi > 27.71) -> 0,\n",
" if (ap_hi <= 129.5) and (age <= 54.65) and (cholesterol > 2.5) and (bmi <= 29.043) -> 0,\n",
" if (ap_hi <= 129.5) and (ap_hi > 115.0) and (age <= 54.65) and (cholesterol > 2.5) and (bmi <= 29.043) -> 0,\n",
" if (ap_hi <= 129.5) and (age <= 54.65) and (cholesterol > 2.5) and (bmi > 29.043) -> 0,\n",
" if (ap_hi <= 129.5) and (age <= 54.65) and (age > 39.751) and (cholesterol > 2.5) and (bmi > 29.043) -> 1,\n",
" if (ap_hi <= 129.5) and (age <= 54.65) and (age > 54.008) and (cholesterol > 2.5) and (bmi > 29.043) and (bmi <= 35.021) -> 0,\n",
" if (ap_hi <= 129.5) and (age <= 54.65) and (age > 54.008) and (cholesterol > 2.5) and (bmi > 29.043) -> 1,\n",
" if (ap_hi <= 129.5) and (age > 54.65) and (age <= 60.707) and (cholesterol <= 2.5) and (bmi <= 23.329) -> 0,\n",
" if (ap_hi <= 129.5) and (age > 54.65) and (age <= 60.707) and (cholesterol <= 2.5) and (bmi > 23.329) -> 0,\n",
" if (ap_hi <= 129.5) and (ap_hi > 118.5) and (age > 54.65) and (age <= 60.707) and (cholesterol <= 2.5) and (bmi <= 32.886) -> 0,\n",
" if (ap_hi <= 129.5) and (ap_hi > 118.5) and (age > 54.65) and (age <= 60.707) and (cholesterol <= 2.5) and (bmi > 32.886) -> 1,\n",
" if (ap_hi <= 129.5) and (age > 54.65) and (age <= 64.308) and (cholesterol <= 2.5) and (bmi <= 20.512) -> 0,\n",
" if (ap_hi <= 129.5) and (age > 54.65) and (cholesterol <= 2.5) and (bmi <= 20.512) -> 1,\n",
" if (ap_hi <= 129.5) and (age > 54.65) and (cholesterol <= 2.5) and (bmi > 20.512) -> 0,\n",
" if (ap_hi <= 129.5) and (ap_hi > 115.5) and (age > 54.65) and (cholesterol <= 2.5) and (bmi > 20.512) -> 1,\n",
" if (ap_hi <= 129.5) and (age > 54.65) and (cholesterol > 2.5) and (bmi <= 26.032) -> 1,\n",
" if (ap_hi <= 129.5) and (age > 54.65) and (cholesterol > 2.5) and (bmi <= 26.032) and (bmi > 25.912) -> 0,\n",
" if (ap_hi <= 129.5) and (age > 54.65) and (age <= 59.39) and (cholesterol > 2.5) and (bmi > 26.032) and (bmi <= 35.932) -> 1,\n",
" if (ap_hi <= 129.5) and (age > 54.65) and (age <= 59.39) and (cholesterol > 2.5) and (bmi > 26.032) -> 1,\n",
" if (ap_hi <= 129.5) and (age > 54.65) and (cholesterol > 2.5) and (bmi > 26.032) and (bmi <= 35.121) -> 1,\n",
" if (ap_hi <= 129.5) and (age > 54.65) and (cholesterol > 2.5) and (bmi > 26.032) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol <= 2.5) and (age <= 59.536) and (bmi <= 21.637) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol <= 2.5) and (age <= 59.536) and (bmi <= 21.637) and (bmi > 17.3) -> 0,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol <= 2.5) and (age <= 59.536) and (bmi > 21.637) -> 0,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol <= 2.5) and (age <= 59.536) and (age > 39.989) and (bmi > 21.637) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol <= 2.5) and (age > 59.536) and (age <= 62.463) and (bmi <= 20.614) -> 0,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol <= 2.5) and (age > 59.536) and (age <= 62.463) and (bmi > 20.614) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol <= 2.5) and (age > 59.536) and (age <= 63.998) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol <= 2.5) and (age > 59.536) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol > 2.5) and (bmi <= 30.744) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol > 2.5) and (bmi <= 30.744) and (bmi > 23.927) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol > 2.5) and (bmi > 30.744) and (bmi <= 32.049) and (age <= 43.632) -> 0,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol > 2.5) and (bmi > 30.744) and (bmi <= 32.049) and (age > 43.632) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol > 2.5) and (bmi > 30.744) and (bmi <= 32.337) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol > 2.5) and (bmi > 30.744) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi <= 149.5) and (age <= 39.558) and (bmi <= 38.186) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi <= 149.5) and (age <= 39.558) and (age > 39.538) and (bmi <= 38.186) -> 0,\n",
" if (ap_hi > 129.5) and (ap_hi <= 149.5) and (age <= 39.558) and (bmi > 38.186) and (bmi <= 50.547) -> 0,\n",
" if (ap_hi > 129.5) and (ap_hi <= 149.5) and (age <= 39.558) and (bmi > 38.186) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi <= 149.5) and (age > 39.558) and (age <= 47.569) and (bmi <= 19.231) -> 0,\n",
" if (ap_hi > 129.5) and (ap_hi <= 149.5) and (age > 39.558) and (age <= 47.569) and (bmi > 19.231) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi <= 149.5) and (age > 39.558) and (age <= 61.572) -> 1,\n",
" if (ap_hi > 129.5) and (ap_hi <= 149.5) and (age > 39.558) -> 1,\n",
" if (ap_hi > 129.5) and (bmi <= 20.482) and (age <= 64.269) -> 1,\n",
" if (ap_hi > 129.5) and (bmi <= 20.482) and (age <= 64.269) and (age > 55.817) -> 1,\n",
" if (ap_hi > 129.5) and (bmi <= 20.482) and (age > 64.269) -> 0,\n",
" if (ap_hi > 129.5) and (bmi > 20.482) and (age <= 64.351) -> 1,\n",
" if (ap_hi > 129.5) and (bmi > 20.482) and (age <= 64.351) and (age > 49.818) -> 1,\n",
" if (ap_hi > 129.5) and (bmi > 20.482) and (bmi <= 36.796) and (age > 64.351) -> 1,\n",
" if (ap_hi > 129.5) and (bmi > 20.482) and (age > 64.351) -> 0]"
]
},
"execution_count": 102,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"rules = [\n",
" rule for rule in rules if rule.get_consequent() == 0 or rule.get_consequent() == 1\n",
"]\n",
"display(len(rules))\n",
"rules"
]
},
{
"cell_type": "code",
"execution_count": 103,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['(age <= 39.558)', '(age <= 43.632)', '(age <= 47.569)', '(age <= 54.65)', '(age <= 59.39)', '(age <= 59.536)', '(age <= 60.707)', '(age <= 61.572)', '(age <= 62.463)', '(age <= 63.998)', '(age <= 64.269)', '(age <= 64.308)', '(age <= 64.351)', '(age > 39.538)', '(age > 39.558)', '(age > 39.751)', '(age > 39.989)', '(age > 43.632)', '(age > 43.792)', '(age > 49.818)', '(age > 54.008)', '(age > 54.65)', '(age > 55.817)', '(age > 59.536)', '(age > 64.269)', '(age > 64.351)', '(ap_hi <= 129.5)', '(ap_hi <= 138.5)', '(ap_hi <= 149.5)', '(ap_hi > 114.5)', '(ap_hi > 115.0)', '(ap_hi > 115.5)', '(ap_hi > 118.5)', '(ap_hi > 119.5)', '(ap_hi > 129.5)', '(bmi <= 19.231)', '(bmi <= 20.482)', '(bmi <= 20.512)', '(bmi <= 20.614)', '(bmi <= 21.637)', '(bmi <= 22.045)', '(bmi <= 23.329)', '(bmi <= 26.032)', '(bmi <= 27.71)', '(bmi <= 28.874)', '(bmi <= 29.043)', '(bmi <= 30.744)', '(bmi <= 32.049)', '(bmi <= 32.337)', '(bmi <= 32.886)', '(bmi <= 35.021)', '(bmi <= 35.121)', '(bmi <= 35.932)', '(bmi <= 36.796)', '(bmi <= 38.186)', '(bmi <= 50.547)', '(bmi > 17.3)', '(bmi > 19.231)', '(bmi > 20.482)', '(bmi > 20.512)', '(bmi > 20.614)', '(bmi > 21.637)', '(bmi > 22.045)', '(bmi > 23.329)', '(bmi > 23.927)', '(bmi > 25.912)', '(bmi > 26.032)', '(bmi > 27.71)', '(bmi > 28.874)', '(bmi > 29.043)', '(bmi > 30.744)', '(bmi > 32.886)', '(bmi > 38.186)', '(cholesterol <= 2.5)', '(cholesterol > 1.5)', '(cholesterol > 2.5)']\n"
]
},
{
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" .dataframe thead th {\n",
" text-align: right;\n",
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>(age &lt;= 39.558)</th>\n",
" <th>(age &lt;= 43.632)</th>\n",
" <th>(age &lt;= 47.569)</th>\n",
" <th>(age &lt;= 54.65)</th>\n",
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" <th>(bmi &gt; 32.886)</th>\n",
" <th>(bmi &gt; 38.186)</th>\n",
" <th>(cholesterol &lt;= 2.5)</th>\n",
" <th>(cholesterol &gt; 1.5)</th>\n",
" <th>(cholesterol &gt; 2.5)</th>\n",
" <th>consequent</th>\n",
" </tr>\n",
" <tr>\n",
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],
"text/plain": [
" (age <= 39.558) \\\n",
"rule \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 0 \n",
"if (ap_hi <= 129.5) and (ap_hi > 114.5) and (ag... 0 \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 0 \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 0 \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (age... 0 \n",
"\n",
" (age <= 43.632) \\\n",
"rule \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 0 \n",
"if (ap_hi <= 129.5) and (ap_hi > 114.5) and (ag... 0 \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 0 \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 0 \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (age... 0 \n",
"\n",
" (age <= 47.569) \\\n",
"rule \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 0 \n",
"if (ap_hi <= 129.5) and (ap_hi > 114.5) and (ag... 0 \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 0 \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 0 \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (age... 0 \n",
"\n",
" (age <= 54.65) \\\n",
"rule \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 1 \n",
"if (ap_hi <= 129.5) and (ap_hi > 114.5) and (ag... 1 \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 1 \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 1 \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (age... 1 \n",
"\n",
" (age <= 59.39) \\\n",
"rule \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 0 \n",
"if (ap_hi <= 129.5) and (ap_hi > 114.5) and (ag... 0 \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 0 \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 0 \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (age... 0 \n",
"\n",
" (age <= 59.536) \\\n",
"rule \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 0 \n",
"if (ap_hi <= 129.5) and (ap_hi > 114.5) and (ag... 0 \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 0 \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 0 \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (age... 0 \n",
"\n",
" (age <= 60.707) \\\n",
"rule \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 0 \n",
"if (ap_hi <= 129.5) and (ap_hi > 114.5) and (ag... 0 \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 0 \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 0 \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (age... 0 \n",
"\n",
" (age <= 61.572) \\\n",
"rule \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 0 \n",
"if (ap_hi <= 129.5) and (ap_hi > 114.5) and (ag... 0 \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 0 \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 0 \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (age... 0 \n",
"\n",
" (age <= 62.463) \\\n",
"rule \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 0 \n",
"if (ap_hi <= 129.5) and (ap_hi > 114.5) and (ag... 0 \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 0 \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 0 \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (age... 0 \n",
"\n",
" (age <= 63.998) ... \\\n",
"rule ... \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 0 ... \n",
"if (ap_hi <= 129.5) and (ap_hi > 114.5) and (ag... 0 ... \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 0 ... \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 0 ... \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (age... 0 ... \n",
"\n",
" (bmi > 27.71) \\\n",
"rule \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 0 \n",
"if (ap_hi <= 129.5) and (ap_hi > 114.5) and (ag... 0 \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 0 \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 0 \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (age... 0 \n",
"\n",
" (bmi > 28.874) \\\n",
"rule \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 0 \n",
"if (ap_hi <= 129.5) and (ap_hi > 114.5) and (ag... 0 \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 0 \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 1 \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (age... 0 \n",
"\n",
" (bmi > 29.043) \\\n",
"rule \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 0 \n",
"if (ap_hi <= 129.5) and (ap_hi > 114.5) and (ag... 0 \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 0 \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 0 \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (age... 0 \n",
"\n",
" (bmi > 30.744) \\\n",
"rule \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 0 \n",
"if (ap_hi <= 129.5) and (ap_hi > 114.5) and (ag... 0 \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 0 \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 0 \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (age... 0 \n",
"\n",
" (bmi > 32.886) \\\n",
"rule \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 0 \n",
"if (ap_hi <= 129.5) and (ap_hi > 114.5) and (ag... 0 \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 0 \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 0 \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (age... 0 \n",
"\n",
" (bmi > 38.186) \\\n",
"rule \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 0 \n",
"if (ap_hi <= 129.5) and (ap_hi > 114.5) and (ag... 0 \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 0 \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 0 \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (age... 0 \n",
"\n",
" (cholesterol <= 2.5) \\\n",
"rule \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 1 \n",
"if (ap_hi <= 129.5) and (ap_hi > 114.5) and (ag... 1 \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 1 \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 1 \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (age... 1 \n",
"\n",
" (cholesterol > 1.5) \\\n",
"rule \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 0 \n",
"if (ap_hi <= 129.5) and (ap_hi > 114.5) and (ag... 0 \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 1 \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 1 \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (age... 0 \n",
"\n",
" (cholesterol > 2.5) \\\n",
"rule \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 0 \n",
"if (ap_hi <= 129.5) and (ap_hi > 114.5) and (ag... 0 \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 0 \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 0 \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (age... 0 \n",
"\n",
" consequent \n",
"rule \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 0 \n",
"if (ap_hi <= 129.5) and (ap_hi > 114.5) and (ag... 0 \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 0 \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cho... 0 \n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (age... 0 \n",
"\n",
"[5 rows x 77 columns]"
]
},
"execution_count": 103,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from src.rules import get_features, vectorize_rules\n",
"\n",
"features = get_features(rules, [])\n",
"print(features)\n",
"\n",
"df_rules = vectorize_rules(rules, features)\n",
"df_rules.head(5)"
]
},
{
"cell_type": "code",
"execution_count": 104,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{2: 0.2028684211063448,\n",
" 3: 0.16350739364416753,\n",
" 4: 0.17115418740422497,\n",
" 5: 0.18051062435509244,\n",
" 6: 0.17312188913678084,\n",
" 7: 0.20265014439953413,\n",
" 8: 0.2470239144182239,\n",
" 9: 0.26319032892830624}"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 400x400 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"'The best clusters count is 9'"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"from src.cluster_helper import draw_best_clusters_plot, get_best_clusters_num\n",
"\n",
"random_state = 9\n",
"\n",
"X = df_rules.copy()\n",
"X = X.drop([\"consequent\"], axis=1)\n",
"\n",
"clusters_score = get_best_clusters_num(X, random_state)\n",
"display(clusters_score)\n",
"\n",
"draw_best_clusters_plot(clusters_score)\n",
"\n",
"clusters_num = sorted(clusters_score.items(), key=lambda x: x[1], reverse=True)[0][0]\n",
"display(f\"The best clusters count is {clusters_num}\")"
]
},
{
"cell_type": "code",
"execution_count": 106,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Кластер 1 (16):\n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cholesterol <= 2.5) -> 0;\n",
"if (ap_hi <= 129.5) and (ap_hi > 114.5) and (age <= 54.65) and (cholesterol <= 2.5) -> 0;\n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cholesterol <= 2.5) and (cholesterol > 1.5) and (bmi <= 28.874) -> 0;\n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cholesterol <= 2.5) and (cholesterol > 1.5) and (bmi > 28.874) -> 0;\n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (age > 43.792) and (cholesterol <= 2.5) and (bmi <= 22.045) -> 0;\n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (age > 43.792) and (cholesterol <= 2.5) and (bmi > 22.045) -> 0;\n",
"if (ap_hi <= 129.5) and (ap_hi > 119.5) and (age <= 54.65) and (age > 43.792) and (cholesterol <= 2.5) and (bmi <= 27.71) -> 0;\n",
"if (ap_hi <= 129.5) and (ap_hi > 119.5) and (age <= 54.65) and (age > 43.792) and (cholesterol <= 2.5) and (bmi > 27.71) -> 0;\n",
"if (ap_hi <= 129.5) and (age > 54.65) and (age <= 60.707) and (cholesterol <= 2.5) and (bmi <= 23.329) -> 0;\n",
"if (ap_hi <= 129.5) and (age > 54.65) and (age <= 60.707) and (cholesterol <= 2.5) and (bmi > 23.329) -> 0;\n",
"if (ap_hi <= 129.5) and (ap_hi > 118.5) and (age > 54.65) and (age <= 60.707) and (cholesterol <= 2.5) and (bmi <= 32.886) -> 0;\n",
"if (ap_hi <= 129.5) and (ap_hi > 118.5) and (age > 54.65) and (age <= 60.707) and (cholesterol <= 2.5) and (bmi > 32.886) -> 1;\n",
"if (ap_hi <= 129.5) and (age > 54.65) and (age <= 64.308) and (cholesterol <= 2.5) and (bmi <= 20.512) -> 0;\n",
"if (ap_hi <= 129.5) and (age > 54.65) and (cholesterol <= 2.5) and (bmi <= 20.512) -> 1;\n",
"if (ap_hi <= 129.5) and (age > 54.65) and (cholesterol <= 2.5) and (bmi > 20.512) -> 0;\n",
"if (ap_hi <= 129.5) and (ap_hi > 115.5) and (age > 54.65) and (cholesterol <= 2.5) and (bmi > 20.512) -> 1\n",
"--------\n",
"Кластер 2 (8):\n",
"if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol <= 2.5) and (age <= 59.536) and (bmi <= 21.637) -> 1;\n",
"if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol <= 2.5) and (age <= 59.536) and (bmi <= 21.637) and (bmi > 17.3) -> 0;\n",
"if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol <= 2.5) and (age <= 59.536) and (bmi > 21.637) -> 0;\n",
"if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol <= 2.5) and (age <= 59.536) and (age > 39.989) and (bmi > 21.637) -> 1;\n",
"if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol <= 2.5) and (age > 59.536) and (age <= 62.463) and (bmi <= 20.614) -> 0;\n",
"if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol <= 2.5) and (age > 59.536) and (age <= 62.463) and (bmi > 20.614) -> 1;\n",
"if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol <= 2.5) and (age > 59.536) and (age <= 63.998) -> 1;\n",
"if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol <= 2.5) and (age > 59.536) -> 1\n",
"--------\n",
"Кластер 3 (6):\n",
"if (ap_hi <= 129.5) and (age > 54.65) and (cholesterol > 2.5) and (bmi <= 26.032) -> 1;\n",
"if (ap_hi <= 129.5) and (age > 54.65) and (cholesterol > 2.5) and (bmi <= 26.032) and (bmi > 25.912) -> 0;\n",
"if (ap_hi <= 129.5) and (age > 54.65) and (age <= 59.39) and (cholesterol > 2.5) and (bmi > 26.032) and (bmi <= 35.932) -> 1;\n",
"if (ap_hi <= 129.5) and (age > 54.65) and (age <= 59.39) and (cholesterol > 2.5) and (bmi > 26.032) -> 1;\n",
"if (ap_hi <= 129.5) and (age > 54.65) and (cholesterol > 2.5) and (bmi > 26.032) and (bmi <= 35.121) -> 1;\n",
"if (ap_hi <= 129.5) and (age > 54.65) and (cholesterol > 2.5) and (bmi > 26.032) -> 1\n",
"--------\n",
"Кластер 4 (3):\n",
"if (ap_hi > 129.5) and (bmi <= 20.482) and (age <= 64.269) -> 1;\n",
"if (ap_hi > 129.5) and (bmi <= 20.482) and (age <= 64.269) and (age > 55.817) -> 1;\n",
"if (ap_hi > 129.5) and (bmi <= 20.482) and (age > 64.269) -> 0\n",
"--------\n",
"Кластер 5 (4):\n",
"if (ap_hi > 129.5) and (ap_hi <= 149.5) and (age <= 39.558) and (bmi <= 38.186) -> 1;\n",
"if (ap_hi > 129.5) and (ap_hi <= 149.5) and (age <= 39.558) and (age > 39.538) and (bmi <= 38.186) -> 0;\n",
"if (ap_hi > 129.5) and (ap_hi <= 149.5) and (age <= 39.558) and (bmi > 38.186) and (bmi <= 50.547) -> 0;\n",
"if (ap_hi > 129.5) and (ap_hi <= 149.5) and (age <= 39.558) and (bmi > 38.186) -> 1\n",
"--------\n",
"Кластер 6 (6):\n",
"if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol > 2.5) and (bmi <= 30.744) -> 1;\n",
"if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol > 2.5) and (bmi <= 30.744) and (bmi > 23.927) -> 1;\n",
"if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol > 2.5) and (bmi > 30.744) and (bmi <= 32.049) and (age <= 43.632) -> 0;\n",
"if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol > 2.5) and (bmi > 30.744) and (bmi <= 32.049) and (age > 43.632) -> 1;\n",
"if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol > 2.5) and (bmi > 30.744) and (bmi <= 32.337) -> 1;\n",
"if (ap_hi > 129.5) and (ap_hi <= 138.5) and (cholesterol > 2.5) and (bmi > 30.744) -> 1\n",
"--------\n",
"Кластер 7 (4):\n",
"if (ap_hi > 129.5) and (ap_hi <= 149.5) and (age > 39.558) and (age <= 47.569) and (bmi <= 19.231) -> 0;\n",
"if (ap_hi > 129.5) and (ap_hi <= 149.5) and (age > 39.558) and (age <= 47.569) and (bmi > 19.231) -> 1;\n",
"if (ap_hi > 129.5) and (ap_hi <= 149.5) and (age > 39.558) and (age <= 61.572) -> 1;\n",
"if (ap_hi > 129.5) and (ap_hi <= 149.5) and (age > 39.558) -> 1\n",
"--------\n",
"Кластер 8 (6):\n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cholesterol > 2.5) and (bmi <= 29.043) -> 0;\n",
"if (ap_hi <= 129.5) and (ap_hi > 115.0) and (age <= 54.65) and (cholesterol > 2.5) and (bmi <= 29.043) -> 0;\n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (cholesterol > 2.5) and (bmi > 29.043) -> 0;\n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (age > 39.751) and (cholesterol > 2.5) and (bmi > 29.043) -> 1;\n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (age > 54.008) and (cholesterol > 2.5) and (bmi > 29.043) and (bmi <= 35.021) -> 0;\n",
"if (ap_hi <= 129.5) and (age <= 54.65) and (age > 54.008) and (cholesterol > 2.5) and (bmi > 29.043) -> 1\n",
"--------\n",
"Кластер 9 (4):\n",
"if (ap_hi > 129.5) and (bmi > 20.482) and (age <= 64.351) -> 1;\n",
"if (ap_hi > 129.5) and (bmi > 20.482) and (age <= 64.351) and (age > 49.818) -> 1;\n",
"if (ap_hi > 129.5) and (bmi > 20.482) and (bmi <= 36.796) and (age > 64.351) -> 1;\n",
"if (ap_hi > 129.5) and (bmi > 20.482) and (age > 64.351) -> 0\n",
"--------\n"
]
}
],
"source": [
"from sklearn import cluster\n",
"\n",
"from src.cluster_helper import print_cluster_result\n",
"\n",
"kmeans = cluster.KMeans(n_clusters=clusters_num, random_state=random_state)\n",
"kmeans.fit(X)\n",
"\n",
"print_cluster_result(X, clusters_num, kmeans.labels_)"
]
},
{
"cell_type": "code",
"execution_count": 107,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[[if (ap_hi = 7) and (age = 29.564) and (cholesterol = 1) -> 0,\n",
" if (ap_hi = 122.0) and (age = 29.564) and (cholesterol = 1) -> 0,\n",
" if (ap_hi = 7) and (age = 29.564) and (cholesterol = 2.0) and (bmi = 3.472) -> 0,\n",
" if (ap_hi = 7) and (age = 29.564) and (cholesterol = 2.0) and (bmi = 298.667) -> 0,\n",
" if (ap_hi = 7) and (age = 49.221) and (cholesterol = 1) and (bmi = 3.472) -> 0,\n",
" if (ap_hi = 7) and (age = 49.221) and (cholesterol = 1) and (bmi = 298.667) -> 0,\n",
" if (ap_hi = 124.5) and (age = 49.221) and (cholesterol = 1) and (bmi = 3.472) -> 0,\n",
" if (ap_hi = 124.5) and (age = 49.221) and (cholesterol = 1) and (bmi = 298.667) -> 0,\n",
" if (ap_hi = 7) and (age = 57.679) and (cholesterol = 1) and (bmi = 3.472) -> 0,\n",
" if (ap_hi = 7) and (age = 57.679) and (cholesterol = 1) and (bmi = 298.667) -> 0,\n",
" if (ap_hi = 124.0) and (age = 57.679) and (cholesterol = 1) and (bmi = 3.472) -> 0,\n",
" if (ap_hi = 124.0) and (age = 57.679) and (cholesterol = 1) and (bmi = 298.667) -> 1,\n",
" if (ap_hi = 7) and (age = 59.479) and (cholesterol = 1) and (bmi = 3.472) -> 0,\n",
" if (ap_hi = 7) and (age = 64.924) and (cholesterol = 1) and (bmi = 3.472) -> 1,\n",
" if (ap_hi = 7) and (age = 64.924) and (cholesterol = 1) and (bmi = 298.667) -> 0,\n",
" if (ap_hi = 122.5) and (age = 64.924) and (cholesterol = 1) and (bmi = 298.667) -> 1],\n",
" [if (ap_hi = 134.0) and (cholesterol = 1) and (age = 29.564) and (bmi = 3.472) -> 1,\n",
" if (ap_hi = 134.0) and (cholesterol = 1) and (age = 29.564) and (bmi = 19.469) -> 0,\n",
" if (ap_hi = 134.0) and (cholesterol = 1) and (age = 29.564) and (bmi = 298.667) -> 0,\n",
" if (ap_hi = 134.0) and (cholesterol = 1) and (age = 49.762) and (bmi = 298.667) -> 1,\n",
" if (ap_hi = 134.0) and (cholesterol = 1) and (age = 61.0) and (bmi = 3.472) -> 0,\n",
" if (ap_hi = 134.0) and (cholesterol = 1) and (age = 61.0) and (bmi = 298.667) -> 1,\n",
" if (ap_hi = 134.0) and (cholesterol = 1) and (age = 61.767) -> 1,\n",
" if (ap_hi = 134.0) and (cholesterol = 1) and (age = 64.924) -> 1],\n",
" [if (ap_hi = 7) and (age = 64.924) and (cholesterol = 3) and (bmi = 3.472) -> 1,\n",
" if (ap_hi = 7) and (age = 64.924) and (cholesterol = 3) and (bmi = 25.972) -> 0,\n",
" if (ap_hi = 7) and (age = 57.02) and (cholesterol = 3) and (bmi = 30.982) -> 1,\n",
" if (ap_hi = 7) and (age = 57.02) and (cholesterol = 3) and (bmi = 298.667) -> 1,\n",
" if (ap_hi = 7) and (age = 64.924) and (cholesterol = 3) and (bmi = 30.577) -> 1,\n",
" if (ap_hi = 7) and (age = 64.924) and (cholesterol = 3) and (bmi = 298.667) -> 1],\n",
" [if (ap_hi = 240) and (bmi = 3.472) and (age = 29.564) -> 1,\n",
" if (ap_hi = 240) and (bmi = 3.472) and (age = 60.043) -> 1,\n",
" if (ap_hi = 240) and (bmi = 3.472) and (age = 64.924) -> 0],\n",
" [if (ap_hi = 139.5) and (age = 29.564) and (bmi = 3.472) -> 1,\n",
" if (ap_hi = 139.5) and (age = 39.548) and (bmi = 3.472) -> 0,\n",
" if (ap_hi = 139.5) and (age = 29.564) and (bmi = 44.367) -> 0,\n",
" if (ap_hi = 139.5) and (age = 29.564) and (bmi = 298.667) -> 1],\n",
" [if (ap_hi = 134.0) and (cholesterol = 3) and (bmi = 3.472) -> 1,\n",
" if (ap_hi = 134.0) and (cholesterol = 3) and (bmi = 27.336) -> 1,\n",
" if (ap_hi = 134.0) and (cholesterol = 3) and (bmi = 31.396) and (age = 29.564) -> 0,\n",
" if (ap_hi = 134.0) and (cholesterol = 3) and (bmi = 31.396) and (age = 64.924) -> 1,\n",
" if (ap_hi = 134.0) and (cholesterol = 3) and (bmi = 31.54) -> 1,\n",
" if (ap_hi = 134.0) and (cholesterol = 3) and (bmi = 298.667) -> 1],\n",
" [if (ap_hi = 139.5) and (age = 43.563) and (bmi = 3.472) -> 0,\n",
" if (ap_hi = 139.5) and (age = 43.563) and (bmi = 298.667) -> 1,\n",
" if (ap_hi = 139.5) and (age = 50.565) -> 1,\n",
" if (ap_hi = 139.5) and (age = 64.924) -> 1],\n",
" [if (ap_hi = 7) and (age = 29.564) and (cholesterol = 3) and (bmi = 3.472) -> 0,\n",
" if (ap_hi = 122.25) and (age = 29.564) and (cholesterol = 3) and (bmi = 3.472) -> 0,\n",
" if (ap_hi = 7) and (age = 29.564) and (cholesterol = 3) and (bmi = 298.667) -> 0,\n",
" if (ap_hi = 7) and (age = 47.2) and (cholesterol = 3) and (bmi = 298.667) -> 1,\n",
" if (ap_hi = 7) and (age = 54.329) and (cholesterol = 3) and (bmi = 32.032) -> 0,\n",
" if (ap_hi = 7) and (age = 54.329) and (cholesterol = 3) and (bmi = 298.667) -> 1],\n",
" [if (ap_hi = 240) and (bmi = 298.667) and (age = 29.564) -> 1,\n",
" if (ap_hi = 240) and (bmi = 298.667) and (age = 57.084) -> 1,\n",
" if (ap_hi = 240) and (bmi = 28.639) and (age = 64.924) -> 1,\n",
" if (ap_hi = 240) and (bmi = 298.667) and (age = 64.924) -> 0]]"
]
},
"execution_count": 107,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from src.rules import simplify_and_group_rules\n",
"\n",
"clustered_rules = simplify_and_group_rules(\n",
" df, rules, clusters_num, kmeans.labels_\n",
")\n",
"clustered_rules"
]
},
{
"cell_type": "code",
"execution_count": 108,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>count</th>\n",
" <th>mean</th>\n",
" <th>std</th>\n",
" <th>min</th>\n",
" <th>25%</th>\n",
" <th>50%</th>\n",
" <th>75%</th>\n",
" <th>max</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>age</th>\n",
" <td>68985.0</td>\n",
" <td>53.290421</td>\n",
" <td>6.757633</td>\n",
" <td>29.564122</td>\n",
" <td>48.340817</td>\n",
" <td>53.939875</td>\n",
" <td>58.380791</td>\n",
" <td>64.924433</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ap_hi</th>\n",
" <td>68985.0</td>\n",
" <td>126.325027</td>\n",
" <td>17.698621</td>\n",
" <td>7.000000</td>\n",
" <td>120.000000</td>\n",
" <td>120.000000</td>\n",
" <td>140.000000</td>\n",
" <td>240.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>cholesterol</th>\n",
" <td>68985.0</td>\n",
" <td>1.364384</td>\n",
" <td>0.678691</td>\n",
" <td>1.000000</td>\n",
" <td>1.000000</td>\n",
" <td>1.000000</td>\n",
" <td>1.000000</td>\n",
" <td>3.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>cardio</th>\n",
" <td>68985.0</td>\n",
" <td>0.494905</td>\n",
" <td>0.499978</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>1.000000</td>\n",
" <td>1.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>bmi</th>\n",
" <td>68985.0</td>\n",
" <td>27.524761</td>\n",
" <td>6.081130</td>\n",
" <td>3.471784</td>\n",
" <td>23.875115</td>\n",
" <td>26.346494</td>\n",
" <td>30.119376</td>\n",
" <td>298.666667</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" count mean std min 25% \\\n",
"age 68985.0 53.290421 6.757633 29.564122 48.340817 \n",
"ap_hi 68985.0 126.325027 17.698621 7.000000 120.000000 \n",
"cholesterol 68985.0 1.364384 0.678691 1.000000 1.000000 \n",
"cardio 68985.0 0.494905 0.499978 0.000000 0.000000 \n",
"bmi 68985.0 27.524761 6.081130 3.471784 23.875115 \n",
"\n",
" 50% 75% max \n",
"age 53.939875 58.380791 64.924433 \n",
"ap_hi 120.000000 140.000000 240.000000 \n",
"cholesterol 1.000000 1.000000 3.000000 \n",
"cardio 0.000000 1.000000 1.000000 \n",
"bmi 26.346494 30.119376 298.666667 "
]
},
"execution_count": 108,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.describe().transpose()"
]
},
{
"cell_type": "code",
"execution_count": 109,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/Users/user/Projects/python/fuzzy-rules-generator/.venv/lib/python3.12/site-packages/skfuzzy/control/fuzzyvariable.py:125: UserWarning: FigureCanvasAgg is non-interactive, and thus cannot be shown\n",
" fig.show()\n"
]
},
{
"data": {
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"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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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 numpy as np\n",
"from skfuzzy import control as ctrl\n",
"import skfuzzy as fuzz\n",
"\n",
"age = ctrl.Antecedent(np.arange(29, 65, 0.5), \"age\")\n",
"ap_hi = ctrl.Antecedent(np.arange(7, 240, 0.5), \"ap_hi\")\n",
"cholesterol = ctrl.Antecedent([1, 2, 3], \"cholesterol\")\n",
"bmi = ctrl.Antecedent(np.arange(3, 299, 0.05), \"bmi\")\n",
"cardio = ctrl.Consequent([0, 1], \"cardio\")\n",
"\n",
"age.automf(3, variable_type=\"quant\")\n",
"age.view()\n",
"ap_hi.automf(3, variable_type=\"quant\")\n",
"ap_hi.view()\n",
"cholesterol.automf(3, variable_type=\"quant\")\n",
"cholesterol.view()\n",
"bmi.automf(3, variable_type=\"quant\")\n",
"bmi.view()\n",
"cardio.automf(2, variable_type=\"quant\", names=[\"No\", \"Yes\"])\n",
"cardio.view()"
]
},
{
"cell_type": "code",
"execution_count": 110,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"41"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"[IF (ap_hi[low] AND age[low]) AND cholesterol[low] THEN cardio[No]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF (ap_hi[average] AND age[low]) AND cholesterol[low] THEN cardio[No]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF ((ap_hi[low] AND age[low]) AND cholesterol[average]) AND bmi[low] THEN cardio[No]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF ((ap_hi[low] AND age[low]) AND cholesterol[average]) AND bmi[high] THEN cardio[No]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF ((ap_hi[low] AND age[average]) AND cholesterol[low]) AND bmi[low] THEN cardio[No]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF ((ap_hi[low] AND age[average]) AND cholesterol[low]) AND bmi[high] THEN cardio[No]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF ((ap_hi[average] AND age[average]) AND cholesterol[low]) AND bmi[low] THEN cardio[No]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF ((ap_hi[average] AND age[average]) AND cholesterol[low]) AND bmi[high] THEN cardio[No]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF ((ap_hi[average] AND age[high]) AND cholesterol[low]) AND bmi[low] THEN cardio[No]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF ((ap_hi[low] AND age[high]) AND cholesterol[low]) AND bmi[low] THEN cardio[No]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF ((ap_hi[low] AND age[high]) AND cholesterol[low]) AND bmi[high] THEN cardio[No]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF ((ap_hi[average] AND age[high]) AND cholesterol[low]) AND bmi[high] THEN cardio[Yes]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF ((ap_hi[average] AND cholesterol[low]) AND age[low]) AND bmi[low] THEN cardio[No]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF ((ap_hi[average] AND cholesterol[low]) AND age[low]) AND bmi[high] THEN cardio[No]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF ((ap_hi[average] AND cholesterol[low]) AND age[average]) AND bmi[high] THEN cardio[Yes]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF ((ap_hi[average] AND cholesterol[low]) AND age[high]) AND bmi[low] THEN cardio[No]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF ((ap_hi[average] AND cholesterol[low]) AND age[high]) AND bmi[high] THEN cardio[Yes]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF (ap_hi[average] AND cholesterol[low]) AND age[high] THEN cardio[Yes]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF ((ap_hi[low] AND age[high]) AND cholesterol[high]) AND bmi[low] THEN cardio[Yes]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF ((ap_hi[low] AND age[high]) AND cholesterol[high]) AND bmi[high] THEN cardio[Yes]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF (ap_hi[high] AND bmi[low]) AND age[low] THEN cardio[Yes]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF (ap_hi[high] AND bmi[low]) AND age[high] THEN cardio[Yes]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF (ap_hi[average] AND age[average]) AND bmi[low] THEN cardio[No]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF (ap_hi[average] AND age[low]) AND bmi[low] THEN cardio[No]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF (ap_hi[average] AND age[low]) AND bmi[high] THEN cardio[Yes]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF ((ap_hi[average] AND cholesterol[high]) AND bmi[low]) AND age[low] THEN cardio[No]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF ((ap_hi[average] AND cholesterol[high]) AND bmi[low]) AND age[high] THEN cardio[Yes]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF (ap_hi[average] AND cholesterol[high]) AND bmi[low] THEN cardio[Yes]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF (ap_hi[average] AND cholesterol[high]) AND bmi[high] THEN cardio[Yes]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF (ap_hi[average] AND age[average]) AND bmi[low] THEN cardio[No]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF (ap_hi[average] AND age[average]) AND bmi[high] THEN cardio[Yes]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF ap_hi[average] AND age[average] THEN cardio[Yes]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF ap_hi[average] AND age[high] THEN cardio[Yes]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF ((ap_hi[low] AND age[low]) AND cholesterol[high]) AND bmi[low] THEN cardio[No]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF ((ap_hi[average] AND age[low]) AND cholesterol[high]) AND bmi[low] THEN cardio[No]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF ((ap_hi[low] AND age[low]) AND cholesterol[high]) AND bmi[high] THEN cardio[No]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF ((ap_hi[low] AND age[average]) AND cholesterol[high]) AND bmi[low] THEN cardio[No]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF ((ap_hi[low] AND age[average]) AND cholesterol[high]) AND bmi[high] THEN cardio[Yes]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF (ap_hi[high] AND bmi[high]) AND age[low] THEN cardio[Yes]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF (ap_hi[high] AND bmi[high]) AND age[high] THEN cardio[Yes]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF (ap_hi[high] AND bmi[low]) AND age[high] THEN cardio[Yes]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax]"
]
},
"execution_count": 110,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from src.rules import get_fuzzy_rules\n",
"\n",
"fuzzy_variables = {\n",
" \"age\": age,\n",
" \"ap_hi\": ap_hi,\n",
" \"cholesterol\": cholesterol,\n",
" \"bmi\": bmi,\n",
" \"consequent\": cardio,\n",
"}\n",
"fuzzy_rules = get_fuzzy_rules(clustered_rules, fuzzy_variables)\n",
"\n",
"fuzzy_cntrl = ctrl.ControlSystem(fuzzy_rules)\n",
"\n",
"sim = ctrl.ControlSystemSimulation(fuzzy_cntrl, lenient=False)\n",
"\n",
"display(len(fuzzy_rules))\n",
"fuzzy_rules"
]
},
{
"cell_type": "code",
"execution_count": 111,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"=============\n",
" Antecedents \n",
"=============\n",
"Antecedent: ap_hi = 110\n",
" - low : 0.11397849462365592\n",
" - average : 0.886021505376344\n",
" - high : 0.0\n",
"Antecedent: age = 50.358668\n",
" - low : 0.0\n",
" - average : 0.7966947605633802\n",
" - high : 0.2033052394366198\n",
"Antecedent: cholesterol = 1\n",
" - low : 1.0\n",
" - average : 0.0\n",
" - high : 0.0\n",
"Antecedent: bmi = 21.96712\n",
" - low : 0.8718221321169112\n",
" - average : 0.12817786788308883\n",
" - high : 0.0\n",
"\n",
"=======\n",
" Rules \n",
"=======\n",
"RULE #0:\n",
" IF (ap_hi[low] AND age[low]) AND cholesterol[low] THEN cardio[No]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - ap_hi[low] : 0.11397849462365592\n",
" - age[low] : 0.0\n",
" - cholesterol[low] : 1.0\n",
" (ap_hi[low] AND age[low]) AND cholesterol[low] = 0.0\n",
" Activation (THEN-clause):\n",
" cardio[No] : 0.0\n",
"\n",
"RULE #1:\n",
" IF (ap_hi[average] AND age[low]) AND cholesterol[low] THEN cardio[No]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - ap_hi[average] : 0.886021505376344\n",
" - age[low] : 0.0\n",
" - cholesterol[low] : 1.0\n",
" (ap_hi[average] AND age[low]) AND cholesterol[low] = 0.0\n",
" Activation (THEN-clause):\n",
" cardio[No] : 0.0\n",
"\n",
"RULE #2:\n",
" IF ((ap_hi[low] AND age[low]) AND cholesterol[average]) AND bmi[low] THEN cardio[No]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - ap_hi[low] : 0.11397849462365592\n",
" - age[low] : 0.0\n",
" - cholesterol[average] : 0.0\n",
" - bmi[low] : 0.8718221321169112\n",
" ((ap_hi[low] AND age[low]) AND cholesterol[average]) AND bmi[low] = 0.0\n",
" Activation (THEN-clause):\n",
" cardio[No] : 0.0\n",
"\n",
"RULE #3:\n",
" IF ((ap_hi[low] AND age[low]) AND cholesterol[average]) AND bmi[high] THEN cardio[No]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - ap_hi[low] : 0.11397849462365592\n",
" - age[low] : 0.0\n",
" - cholesterol[average] : 0.0\n",
" - bmi[high] : 0.0\n",
" ((ap_hi[low] AND age[low]) AND cholesterol[average]) AND bmi[high] = 0.0\n",
" Activation (THEN-clause):\n",
" cardio[No] : 0.0\n",
"\n",
"RULE #4:\n",
" IF ((ap_hi[low] AND age[average]) AND cholesterol[low]) AND bmi[low] THEN cardio[No]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - ap_hi[low] : 0.11397849462365592\n",
" - age[average] : 0.7966947605633802\n",
" - cholesterol[low] : 1.0\n",
" - bmi[low] : 0.8718221321169112\n",
" ((ap_hi[low] AND age[average]) AND cholesterol[low]) AND bmi[low] = 0.11397849462365592\n",
" Activation (THEN-clause):\n",
" cardio[No] : 0.11397849462365592\n",
"\n",
"RULE #5:\n",
" IF ((ap_hi[low] AND age[average]) AND cholesterol[low]) AND bmi[high] THEN cardio[No]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - ap_hi[low] : 0.11397849462365592\n",
" - age[average] : 0.7966947605633802\n",
" - cholesterol[low] : 1.0\n",
" - bmi[high] : 0.0\n",
" ((ap_hi[low] AND age[average]) AND cholesterol[low]) AND bmi[high] = 0.0\n",
" Activation (THEN-clause):\n",
" cardio[No] : 0.0\n",
"\n",
"RULE #6:\n",
" IF ((ap_hi[average] AND age[average]) AND cholesterol[low]) AND bmi[low] THEN cardio[No]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - ap_hi[average] : 0.886021505376344\n",
" - age[average] : 0.7966947605633802\n",
" - cholesterol[low] : 1.0\n",
" - bmi[low] : 0.8718221321169112\n",
" ((ap_hi[average] AND age[average]) AND cholesterol[low]) AND bmi[low] = 0.7966947605633802\n",
" Activation (THEN-clause):\n",
" cardio[No] : 0.7966947605633802\n",
"\n",
"RULE #7:\n",
" IF ((ap_hi[average] AND age[average]) AND cholesterol[low]) AND bmi[high] THEN cardio[No]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - ap_hi[average] : 0.886021505376344\n",
" - age[average] : 0.7966947605633802\n",
" - cholesterol[low] : 1.0\n",
" - bmi[high] : 0.0\n",
" ((ap_hi[average] AND age[average]) AND cholesterol[low]) AND bmi[high] = 0.0\n",
" Activation (THEN-clause):\n",
" cardio[No] : 0.0\n",
"\n",
"RULE #8:\n",
" IF ((ap_hi[average] AND age[high]) AND cholesterol[low]) AND bmi[low] THEN cardio[No]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - ap_hi[average] : 0.886021505376344\n",
" - age[high] : 0.2033052394366198\n",
" - cholesterol[low] : 1.0\n",
" - bmi[low] : 0.8718221321169112\n",
" ((ap_hi[average] AND age[high]) AND cholesterol[low]) AND bmi[low] = 0.2033052394366198\n",
" Activation (THEN-clause):\n",
" cardio[No] : 0.2033052394366198\n",
"\n",
"RULE #9:\n",
" IF ((ap_hi[low] AND age[high]) AND cholesterol[low]) AND bmi[low] THEN cardio[No]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - ap_hi[low] : 0.11397849462365592\n",
" - age[high] : 0.2033052394366198\n",
" - cholesterol[low] : 1.0\n",
" - bmi[low] : 0.8718221321169112\n",
" ((ap_hi[low] AND age[high]) AND cholesterol[low]) AND bmi[low] = 0.11397849462365592\n",
" Activation (THEN-clause):\n",
" cardio[No] : 0.11397849462365592\n",
"\n",
"RULE #10:\n",
" IF ((ap_hi[low] AND age[high]) AND cholesterol[low]) AND bmi[high] THEN cardio[No]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - ap_hi[low] : 0.11397849462365592\n",
" - age[high] : 0.2033052394366198\n",
" - cholesterol[low] : 1.0\n",
" - bmi[high] : 0.0\n",
" ((ap_hi[low] AND age[high]) AND cholesterol[low]) AND bmi[high] = 0.0\n",
" Activation (THEN-clause):\n",
" cardio[No] : 0.0\n",
"\n",
"RULE #11:\n",
" IF ((ap_hi[average] AND age[high]) AND cholesterol[low]) AND bmi[high] THEN cardio[Yes]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - ap_hi[average] : 0.886021505376344\n",
" - age[high] : 0.2033052394366198\n",
" - cholesterol[low] : 1.0\n",
" - bmi[high] : 0.0\n",
" ((ap_hi[average] AND age[high]) AND cholesterol[low]) AND bmi[high] = 0.0\n",
" Activation (THEN-clause):\n",
" cardio[Yes] : 0.0\n",
"\n",
"RULE #12:\n",
" IF ((ap_hi[average] AND cholesterol[low]) AND age[low]) AND bmi[low] THEN cardio[No]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - ap_hi[average] : 0.886021505376344\n",
" - cholesterol[low] : 1.0\n",
" - age[low] : 0.0\n",
" - bmi[low] : 0.8718221321169112\n",
" ((ap_hi[average] AND cholesterol[low]) AND age[low]) AND bmi[low] = 0.0\n",
" Activation (THEN-clause):\n",
" cardio[No] : 0.0\n",
"\n",
"RULE #13:\n",
" IF ((ap_hi[average] AND cholesterol[low]) AND age[low]) AND bmi[high] THEN cardio[No]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - ap_hi[average] : 0.886021505376344\n",
" - cholesterol[low] : 1.0\n",
" - age[low] : 0.0\n",
" - bmi[high] : 0.0\n",
" ((ap_hi[average] AND cholesterol[low]) AND age[low]) AND bmi[high] = 0.0\n",
" Activation (THEN-clause):\n",
" cardio[No] : 0.0\n",
"\n",
"RULE #14:\n",
" IF ((ap_hi[average] AND cholesterol[low]) AND age[average]) AND bmi[high] THEN cardio[Yes]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - ap_hi[average] : 0.886021505376344\n",
" - cholesterol[low] : 1.0\n",
" - age[average] : 0.7966947605633802\n",
" - bmi[high] : 0.0\n",
" ((ap_hi[average] AND cholesterol[low]) AND age[average]) AND bmi[high] = 0.0\n",
" Activation (THEN-clause):\n",
" cardio[Yes] : 0.0\n",
"\n",
"RULE #15:\n",
" IF ((ap_hi[average] AND cholesterol[low]) AND age[high]) AND bmi[low] THEN cardio[No]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - ap_hi[average] : 0.886021505376344\n",
" - cholesterol[low] : 1.0\n",
" - age[high] : 0.2033052394366198\n",
" - bmi[low] : 0.8718221321169112\n",
" ((ap_hi[average] AND cholesterol[low]) AND age[high]) AND bmi[low] = 0.2033052394366198\n",
" Activation (THEN-clause):\n",
" cardio[No] : 0.2033052394366198\n",
"\n",
"RULE #16:\n",
" IF ((ap_hi[average] AND cholesterol[low]) AND age[high]) AND bmi[high] THEN cardio[Yes]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - ap_hi[average] : 0.886021505376344\n",
" - cholesterol[low] : 1.0\n",
" - age[high] : 0.2033052394366198\n",
" - bmi[high] : 0.0\n",
" ((ap_hi[average] AND cholesterol[low]) AND age[high]) AND bmi[high] = 0.0\n",
" Activation (THEN-clause):\n",
" cardio[Yes] : 0.0\n",
"\n",
"RULE #17:\n",
" IF (ap_hi[average] AND cholesterol[low]) AND age[high] THEN cardio[Yes]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - ap_hi[average] : 0.886021505376344\n",
" - cholesterol[low] : 1.0\n",
" - age[high] : 0.2033052394366198\n",
" (ap_hi[average] AND cholesterol[low]) AND age[high] = 0.2033052394366198\n",
" Activation (THEN-clause):\n",
" cardio[Yes] : 0.2033052394366198\n",
"\n",
"RULE #18:\n",
" IF ((ap_hi[low] AND age[high]) AND cholesterol[high]) AND bmi[low] THEN cardio[Yes]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - ap_hi[low] : 0.11397849462365592\n",
" - age[high] : 0.2033052394366198\n",
" - cholesterol[high] : 0.0\n",
" - bmi[low] : 0.8718221321169112\n",
" ((ap_hi[low] AND age[high]) AND cholesterol[high]) AND bmi[low] = 0.0\n",
" Activation (THEN-clause):\n",
" cardio[Yes] : 0.0\n",
"\n",
"RULE #19:\n",
" IF ((ap_hi[low] AND age[high]) AND cholesterol[high]) AND bmi[high] THEN cardio[Yes]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - ap_hi[low] : 0.11397849462365592\n",
" - age[high] : 0.2033052394366198\n",
" - cholesterol[high] : 0.0\n",
" - bmi[high] : 0.0\n",
" ((ap_hi[low] AND age[high]) AND cholesterol[high]) AND bmi[high] = 0.0\n",
" Activation (THEN-clause):\n",
" cardio[Yes] : 0.0\n",
"\n",
"RULE #20:\n",
" IF (ap_hi[high] AND bmi[low]) AND age[low] THEN cardio[Yes]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - ap_hi[high] : 0.0\n",
" - bmi[low] : 0.8718221321169112\n",
" - age[low] : 0.0\n",
" (ap_hi[high] AND bmi[low]) AND age[low] = 0.0\n",
" Activation (THEN-clause):\n",
" cardio[Yes] : 0.0\n",
"\n",
"RULE #21:\n",
" IF (ap_hi[high] AND bmi[low]) AND age[high] THEN cardio[Yes]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - ap_hi[high] : 0.0\n",
" - bmi[low] : 0.8718221321169112\n",
" - age[high] : 0.2033052394366198\n",
" (ap_hi[high] AND bmi[low]) AND age[high] = 0.0\n",
" Activation (THEN-clause):\n",
" cardio[Yes] : 0.0\n",
"\n",
"RULE #22:\n",
" IF (ap_hi[average] AND age[average]) AND bmi[low] THEN cardio[No]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - ap_hi[average] : 0.886021505376344\n",
" - age[average] : 0.7966947605633802\n",
" - bmi[low] : 0.8718221321169112\n",
" (ap_hi[average] AND age[average]) AND bmi[low] = 0.7966947605633802\n",
" Activation (THEN-clause):\n",
" cardio[No] : 0.7966947605633802\n",
"\n",
"RULE #23:\n",
" IF (ap_hi[average] AND age[low]) AND bmi[low] THEN cardio[No]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - ap_hi[average] : 0.886021505376344\n",
" - age[low] : 0.0\n",
" - bmi[low] : 0.8718221321169112\n",
" (ap_hi[average] AND age[low]) AND bmi[low] = 0.0\n",
" Activation (THEN-clause):\n",
" cardio[No] : 0.0\n",
"\n",
"RULE #24:\n",
" IF (ap_hi[average] AND age[low]) AND bmi[high] THEN cardio[Yes]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - ap_hi[average] : 0.886021505376344\n",
" - age[low] : 0.0\n",
" - bmi[high] : 0.0\n",
" (ap_hi[average] AND age[low]) AND bmi[high] = 0.0\n",
" Activation (THEN-clause):\n",
" cardio[Yes] : 0.0\n",
"\n",
"RULE #25:\n",
" IF ((ap_hi[average] AND cholesterol[high]) AND bmi[low]) AND age[low] THEN cardio[No]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - ap_hi[average] : 0.886021505376344\n",
" - cholesterol[high] : 0.0\n",
" - bmi[low] : 0.8718221321169112\n",
" - age[low] : 0.0\n",
" ((ap_hi[average] AND cholesterol[high]) AND bmi[low]) AND age[low] = 0.0\n",
" Activation (THEN-clause):\n",
" cardio[No] : 0.0\n",
"\n",
"RULE #26:\n",
" IF ((ap_hi[average] AND cholesterol[high]) AND bmi[low]) AND age[high] THEN cardio[Yes]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - ap_hi[average] : 0.886021505376344\n",
" - cholesterol[high] : 0.0\n",
" - bmi[low] : 0.8718221321169112\n",
" - age[high] : 0.2033052394366198\n",
" ((ap_hi[average] AND cholesterol[high]) AND bmi[low]) AND age[high] = 0.0\n",
" Activation (THEN-clause):\n",
" cardio[Yes] : 0.0\n",
"\n",
"RULE #27:\n",
" IF (ap_hi[average] AND cholesterol[high]) AND bmi[low] THEN cardio[Yes]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - ap_hi[average] : 0.886021505376344\n",
" - cholesterol[high] : 0.0\n",
" - bmi[low] : 0.8718221321169112\n",
" (ap_hi[average] AND cholesterol[high]) AND bmi[low] = 0.0\n",
" Activation (THEN-clause):\n",
" cardio[Yes] : 0.0\n",
"\n",
"RULE #28:\n",
" IF (ap_hi[average] AND cholesterol[high]) AND bmi[high] THEN cardio[Yes]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - ap_hi[average] : 0.886021505376344\n",
" - cholesterol[high] : 0.0\n",
" - bmi[high] : 0.0\n",
" (ap_hi[average] AND cholesterol[high]) AND bmi[high] = 0.0\n",
" Activation (THEN-clause):\n",
" cardio[Yes] : 0.0\n",
"\n",
"RULE #29:\n",
" IF (ap_hi[average] AND age[average]) AND bmi[low] THEN cardio[No]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - ap_hi[average] : 0.886021505376344\n",
" - age[average] : 0.7966947605633802\n",
" - bmi[low] : 0.8718221321169112\n",
" (ap_hi[average] AND age[average]) AND bmi[low] = 0.7966947605633802\n",
" Activation (THEN-clause):\n",
" cardio[No] : 0.7966947605633802\n",
"\n",
"RULE #30:\n",
" IF (ap_hi[average] AND age[average]) AND bmi[high] THEN cardio[Yes]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - ap_hi[average] : 0.886021505376344\n",
" - age[average] : 0.7966947605633802\n",
" - bmi[high] : 0.0\n",
" (ap_hi[average] AND age[average]) AND bmi[high] = 0.0\n",
" Activation (THEN-clause):\n",
" cardio[Yes] : 0.0\n",
"\n",
"RULE #31:\n",
" IF ap_hi[average] AND age[average] THEN cardio[Yes]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - ap_hi[average] : 0.886021505376344\n",
" - age[average] : 0.7966947605633802\n",
" ap_hi[average] AND age[average] = 0.7966947605633802\n",
" Activation (THEN-clause):\n",
" cardio[Yes] : 0.7966947605633802\n",
"\n",
"RULE #32:\n",
" IF ap_hi[average] AND age[high] THEN cardio[Yes]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - ap_hi[average] : 0.886021505376344\n",
" - age[high] : 0.2033052394366198\n",
" ap_hi[average] AND age[high] = 0.2033052394366198\n",
" Activation (THEN-clause):\n",
" cardio[Yes] : 0.2033052394366198\n",
"\n",
"RULE #33:\n",
" IF ((ap_hi[low] AND age[low]) AND cholesterol[high]) AND bmi[low] THEN cardio[No]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - ap_hi[low] : 0.11397849462365592\n",
" - age[low] : 0.0\n",
" - cholesterol[high] : 0.0\n",
" - bmi[low] : 0.8718221321169112\n",
" ((ap_hi[low] AND age[low]) AND cholesterol[high]) AND bmi[low] = 0.0\n",
" Activation (THEN-clause):\n",
" cardio[No] : 0.0\n",
"\n",
"RULE #34:\n",
" IF ((ap_hi[average] AND age[low]) AND cholesterol[high]) AND bmi[low] THEN cardio[No]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - ap_hi[average] : 0.886021505376344\n",
" - age[low] : 0.0\n",
" - cholesterol[high] : 0.0\n",
" - bmi[low] : 0.8718221321169112\n",
" ((ap_hi[average] AND age[low]) AND cholesterol[high]) AND bmi[low] = 0.0\n",
" Activation (THEN-clause):\n",
" cardio[No] : 0.0\n",
"\n",
"RULE #35:\n",
" IF ((ap_hi[low] AND age[low]) AND cholesterol[high]) AND bmi[high] THEN cardio[No]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - ap_hi[low] : 0.11397849462365592\n",
" - age[low] : 0.0\n",
" - cholesterol[high] : 0.0\n",
" - bmi[high] : 0.0\n",
" ((ap_hi[low] AND age[low]) AND cholesterol[high]) AND bmi[high] = 0.0\n",
" Activation (THEN-clause):\n",
" cardio[No] : 0.0\n",
"\n",
"RULE #36:\n",
" IF ((ap_hi[low] AND age[average]) AND cholesterol[high]) AND bmi[low] THEN cardio[No]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - ap_hi[low] : 0.11397849462365592\n",
" - age[average] : 0.7966947605633802\n",
" - cholesterol[high] : 0.0\n",
" - bmi[low] : 0.8718221321169112\n",
" ((ap_hi[low] AND age[average]) AND cholesterol[high]) AND bmi[low] = 0.0\n",
" Activation (THEN-clause):\n",
" cardio[No] : 0.0\n",
"\n",
"RULE #37:\n",
" IF ((ap_hi[low] AND age[average]) AND cholesterol[high]) AND bmi[high] THEN cardio[Yes]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - ap_hi[low] : 0.11397849462365592\n",
" - age[average] : 0.7966947605633802\n",
" - cholesterol[high] : 0.0\n",
" - bmi[high] : 0.0\n",
" ((ap_hi[low] AND age[average]) AND cholesterol[high]) AND bmi[high] = 0.0\n",
" Activation (THEN-clause):\n",
" cardio[Yes] : 0.0\n",
"\n",
"RULE #38:\n",
" IF (ap_hi[high] AND bmi[high]) AND age[low] THEN cardio[Yes]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - ap_hi[high] : 0.0\n",
" - bmi[high] : 0.0\n",
" - age[low] : 0.0\n",
" (ap_hi[high] AND bmi[high]) AND age[low] = 0.0\n",
" Activation (THEN-clause):\n",
" cardio[Yes] : 0.0\n",
"\n",
"RULE #39:\n",
" IF (ap_hi[high] AND bmi[high]) AND age[high] THEN cardio[Yes]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - ap_hi[high] : 0.0\n",
" - bmi[high] : 0.0\n",
" - age[high] : 0.2033052394366198\n",
" (ap_hi[high] AND bmi[high]) AND age[high] = 0.0\n",
" Activation (THEN-clause):\n",
" cardio[Yes] : 0.0\n",
"\n",
"RULE #40:\n",
" IF (ap_hi[high] AND bmi[low]) AND age[high] THEN cardio[Yes]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - ap_hi[high] : 0.0\n",
" - bmi[low] : 0.8718221321169112\n",
" - age[high] : 0.2033052394366198\n",
" (ap_hi[high] AND bmi[low]) AND age[high] = 0.0\n",
" Activation (THEN-clause):\n",
" cardio[Yes] : 0.0\n",
"\n",
"\n",
"==============================\n",
" Intermediaries and Conquests \n",
"==============================\n",
"Consequent: cardio = 0.5000000000000001\n",
" No:\n",
" Accumulate using accumulation_max : 0.7966947605633802\n",
" Yes:\n",
" Accumulate using accumulation_max : 0.7966947605633802\n",
"\n"
]
},
{
"data": {
"text/plain": [
"np.float64(0.5000000000000001)"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"1"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sim.input[\"age\"] = 50.358668\n",
"sim.input[\"ap_hi\"] = 110\n",
"sim.input[\"cholesterol\"] = 1\n",
"sim.input[\"bmi\"] = 21.967120\n",
"sim.compute()\n",
"sim.print_state()\n",
"display(sim.output[\"cardio\"], 1 if sim.output[\"cardio\"] > 0.5 else 0)\n",
"cardio.view(sim=sim)"
]
},
{
"cell_type": "code",
"execution_count": 112,
"metadata": {},
"outputs": [
{
"data": {
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" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>age</th>\n",
" <th>ap_hi</th>\n",
" <th>cholesterol</th>\n",
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],
"text/plain": [
" age ap_hi cholesterol bmi\n",
"id \n",
"94960 62.014018 120 1 26.892323\n",
"30807 57.745592 120 1 28.393726\n",
"26485 59.670354 120 3 23.875115\n",
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"... ... ... ... ...\n",
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"94833 51.371701 120 1 29.242109\n",
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"81002 55.544300 150 1 27.053803\n",
"\n",
"[55188 rows x 4 columns]"
]
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"metadata": {},
"output_type": "display_data"
},
{
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"metadata": {},
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{
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" <td>100</td>\n",
" <td>3</td>\n",
" <td>21.926126</td>\n",
" </tr>\n",
" <tr>\n",
" <th>88647</th>\n",
" <td>41.517906</td>\n",
" <td>130</td>\n",
" <td>2</td>\n",
" <td>27.764650</td>\n",
" </tr>\n",
" <tr>\n",
" <th>62336</th>\n",
" <td>51.692038</td>\n",
" <td>110</td>\n",
" <td>1</td>\n",
" <td>22.230987</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30330</th>\n",
" <td>47.697404</td>\n",
" <td>100</td>\n",
" <td>1</td>\n",
" <td>22.724403</td>\n",
" </tr>\n",
" <tr>\n",
" <th>62907</th>\n",
" <td>58.597087</td>\n",
" <td>120</td>\n",
" <td>1</td>\n",
" <td>23.828125</td>\n",
" </tr>\n",
" <tr>\n",
" <th>98612</th>\n",
" <td>51.404556</td>\n",
" <td>110</td>\n",
" <td>1</td>\n",
" <td>22.589551</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5767</th>\n",
" <td>62.033184</td>\n",
" <td>120</td>\n",
" <td>1</td>\n",
" <td>23.875115</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14769</th>\n",
" <td>41.506954</td>\n",
" <td>120</td>\n",
" <td>2</td>\n",
" <td>22.948116</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>13797 rows × 4 columns</p>\n",
"</div>"
],
"text/plain": [
" age ap_hi cholesterol bmi\n",
"id \n",
"42270 60.078305 140 1 45.918367\n",
"10780 55.360859 120 2 24.998904\n",
"42436 48.198445 100 3 21.926126\n",
"88647 41.517906 130 2 27.764650\n",
"62336 51.692038 110 1 22.230987\n",
"... ... ... ... ...\n",
"30330 47.697404 100 1 22.724403\n",
"62907 58.597087 120 1 23.828125\n",
"98612 51.404556 110 1 22.589551\n",
"5767 62.033184 120 1 23.875115\n",
"14769 41.506954 120 2 22.948116\n",
"\n",
"[13797 rows x 4 columns]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"id\n",
"42270 1\n",
"10780 0\n",
"42436 1\n",
"88647 1\n",
"62336 0\n",
" ..\n",
"30330 1\n",
"62907 0\n",
"98612 0\n",
"5767 0\n",
"14769 1\n",
"Name: cardio, Length: 13797, dtype: int64"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"from sklearn.model_selection import train_test_split\n",
"\n",
"random_state = 9\n",
"\n",
"def fuzzy_pred(row):\n",
" sim.input[\"age\"] = row[\"age\"]\n",
" sim.input[\"ap_hi\"] = row[\"ap_hi\"]\n",
" sim.input[\"cholesterol\"] = row[\"cholesterol\"]\n",
" sim.input[\"bmi\"] = row[\"bmi\"]\n",
" sim.compute()\n",
" return 1 if sim.output[\"cardio\"] > 0.5 else 0\n",
"\n",
"y = df[\"cardio\"]\n",
"X = df.drop([\"cardio\"], axis=1).copy()\n",
"X_train, X_test, y_train, y_test = train_test_split(\n",
" X, y, test_size=0.2, random_state=random_state\n",
")\n",
"display(X_train, y_train, X_test, y_test)"
]
},
{
"cell_type": "code",
"execution_count": 113,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>age</th>\n",
" <th>ap_hi</th>\n",
" <th>cholesterol</th>\n",
" <th>bmi</th>\n",
" <th>Real</th>\n",
" <th>Inferred</th>\n",
" </tr>\n",
" <tr>\n",
" <th>id</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>42270</th>\n",
" <td>60.078305</td>\n",
" <td>140</td>\n",
" <td>1</td>\n",
" <td>45.918367</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10780</th>\n",
" <td>55.360859</td>\n",
" <td>120</td>\n",
" <td>2</td>\n",
" <td>24.998904</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>42436</th>\n",
" <td>48.198445</td>\n",
" <td>100</td>\n",
" <td>3</td>\n",
" <td>21.926126</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>88647</th>\n",
" <td>41.517906</td>\n",
" <td>130</td>\n",
" <td>2</td>\n",
" <td>27.764650</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>62336</th>\n",
" <td>51.692038</td>\n",
" <td>110</td>\n",
" <td>1</td>\n",
" <td>22.230987</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23904</th>\n",
" <td>53.942613</td>\n",
" <td>120</td>\n",
" <td>1</td>\n",
" <td>35.491690</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>63516</th>\n",
" <td>40.305005</td>\n",
" <td>120</td>\n",
" <td>1</td>\n",
" <td>21.829952</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>84904</th>\n",
" <td>42.561056</td>\n",
" <td>140</td>\n",
" <td>1</td>\n",
" <td>32.882414</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20959</th>\n",
" <td>45.545395</td>\n",
" <td>160</td>\n",
" <td>1</td>\n",
" <td>43.827160</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>77652</th>\n",
" <td>54.115102</td>\n",
" <td>140</td>\n",
" <td>1</td>\n",
" <td>37.105751</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>1000 rows × 6 columns</p>\n",
"</div>"
],
"text/plain": [
" age ap_hi cholesterol bmi Real Inferred\n",
"id \n",
"42270 60.078305 140 1 45.918367 1 1\n",
"10780 55.360859 120 2 24.998904 0 0\n",
"42436 48.198445 100 3 21.926126 1 0\n",
"88647 41.517906 130 2 27.764650 1 0\n",
"62336 51.692038 110 1 22.230987 0 0\n",
"... ... ... ... ... ... ...\n",
"23904 53.942613 120 1 35.491690 1 0\n",
"63516 40.305005 120 1 21.829952 0 0\n",
"84904 42.561056 140 1 32.882414 1 0\n",
"20959 45.545395 160 1 43.827160 1 0\n",
"77652 54.115102 140 1 37.105751 0 0\n",
"\n",
"[1000 rows x 6 columns]"
]
},
"execution_count": 113,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"result_test = X_test.copy()\n",
"result_test[\"Real\"] = y_test\n",
"result_test = result_test.head(1000)\n",
"result_test[\"Inferred\"] = result_test.apply(fuzzy_pred, axis=1)\n",
"result_test"
]
},
{
"cell_type": "code",
"execution_count": 114,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'Precision_test'"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"np.float64(0.5469483568075117)"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"'Recall_test'"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"np.float64(0.4707070707070707)"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"'Accuracy_test'"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"0.545"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"'F1_test'"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"np.float64(0.505971769815418)"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"'Confusion_matrix'"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"array([[312, 193],\n",
" [262, 233]])"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"from sklearn import metrics\n",
"\n",
"display(\n",
" \"Precision_test\",\n",
" metrics.precision_score(result_test[\"Real\"], result_test[\"Inferred\"]),\n",
")\n",
"display(\n",
" \"Recall_test\", metrics.recall_score(result_test[\"Real\"], result_test[\"Inferred\"])\n",
")\n",
"display(\n",
" \"Accuracy_test\",\n",
" metrics.accuracy_score(result_test[\"Real\"], result_test[\"Inferred\"]),\n",
")\n",
"display(\n",
" \"F1_test\", \n",
" metrics.f1_score(result_test[\"Real\"], result_test[\"Inferred\"]),\n",
")\n",
"display(\n",
" \"Confusion_matrix\",\n",
" metrics.confusion_matrix(result_test[\"Real\"], result_test[\"Inferred\"]),\n",
")"
]
}
],
"metadata": {
"kernelspec": {
"display_name": ".venv",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.12.9"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
Reference in New Issue Copy Permalink