is.ulstu.ru/fuzzy-rules-generator
2
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity
d30c1005e9
fuzzy-rules-generator/viscosity_tree.ipynb

1758 lines
306 KiB
Plaintext
Raw Normal View History

initial
2024-11-01 11:04:05 +04:00
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"|--- T <= 32.50\n",
"| |--- TiO2 <= 0.18\n",
"| | |--- Al2O3 <= 0.18\n",
"| | | |--- T <= 22.50\n",
"| | | | |--- TiO2 <= 0.03\n",
"| | | | | |--- Al2O3 <= 0.03\n",
"| | | | | | |--- value: [3.71]\n",
"| | | | | |--- Al2O3 > 0.03\n",
"| | | | | | |--- value: [4.66]\n",
"| | | | |--- TiO2 > 0.03\n",
"| | | | | |--- value: [4.88]\n",
"| | | |--- T > 22.50\n",
"| | | | |--- TiO2 <= 0.03\n",
"| | | | | |--- Al2O3 <= 0.03\n",
"| | | | | | |--- value: [3.18]\n",
"| | | | | |--- Al2O3 > 0.03\n",
"| | | | | | |--- value: [3.38]\n",
"| | | | |--- TiO2 > 0.03\n",
"| | | | | |--- value: [4.24]\n",
"| | |--- Al2O3 > 0.18\n",
"| | | |--- T <= 22.50\n",
"| | | | |--- value: [6.67]\n",
"| | | |--- T > 22.50\n",
"| | | | |--- T <= 27.50\n",
"| | | | | |--- value: [5.59]\n",
"| | | | |--- T > 27.50\n",
"| | | | | |--- value: [4.73]\n",
"| |--- TiO2 > 0.18\n",
"| | |--- T <= 22.50\n",
"| | | |--- value: [7.13]\n",
"| | |--- T > 22.50\n",
"| | | |--- T <= 27.50\n",
"| | | | |--- value: [5.87]\n",
"| | | |--- T > 27.50\n",
"| | | | |--- value: [4.94]\n",
"|--- T > 32.50\n",
"| |--- T <= 47.50\n",
"| | |--- TiO2 <= 0.18\n",
"| | | |--- Al2O3 <= 0.18\n",
"| | | | |--- T <= 42.50\n",
"| | | | | |--- TiO2 <= 0.03\n",
"| | | | | | |--- Al2O3 <= 0.03\n",
"| | | | | | | |--- value: [2.36]\n",
"| | | | | | |--- Al2O3 > 0.03\n",
"| | | | | | | |--- value: [2.68]\n",
"| | | | | |--- TiO2 > 0.03\n",
"| | | | | | |--- T <= 37.50\n",
"| | | | | | | |--- value: [3.12]\n",
"| | | | | | |--- T > 37.50\n",
"| | | | | | | |--- value: [2.65]\n",
"| | | | |--- T > 42.50\n",
"| | | | | |--- TiO2 <= 0.03\n",
"| | | | | | |--- value: [1.83]\n",
"| | | | | |--- TiO2 > 0.03\n",
"| | | | | | |--- value: [2.40]\n",
"| | | |--- Al2O3 > 0.18\n",
"| | | | |--- T <= 37.50\n",
"| | | | | |--- value: [4.12]\n",
"| | | | |--- T > 37.50\n",
"| | | | | |--- value: [3.56]\n",
"| | |--- TiO2 > 0.18\n",
"| | | |--- T <= 40.00\n",
"| | | | |--- value: [4.35]\n",
"| | | |--- T > 40.00\n",
"| | | | |--- value: [3.56]\n",
"| |--- T > 47.50\n",
"| | |--- TiO2 <= 0.18\n",
"| | | |--- Al2O3 <= 0.18\n",
"| | | | |--- T <= 52.50\n",
"| | | | | |--- TiO2 <= 0.03\n",
"| | | | | | |--- Al2O3 <= 0.03\n",
"| | | | | | | |--- value: [1.63]\n",
"| | | | | | |--- Al2O3 > 0.03\n",
"| | | | | | | |--- value: [1.90]\n",
"| | | | | |--- TiO2 > 0.03\n",
"| | | | | | |--- value: [2.11]\n",
"| | | | |--- T > 52.50\n",
"| | | | | |--- T <= 65.00\n",
"| | | | | | |--- TiO2 <= 0.03\n",
"| | | | | | | |--- value: [1.55]\n",
"| | | | | | |--- TiO2 > 0.03\n",
"| | | | | | | |--- value: [1.66]\n",
"| | | | | |--- T > 65.00\n",
"| | | | | | |--- TiO2 <= 0.03\n",
"| | | | | | | |--- value: [1.19]\n",
"| | | | | | |--- TiO2 > 0.03\n",
"| | | | | | | |--- value: [1.29]\n",
"| | | |--- Al2O3 > 0.18\n",
"| | | | |--- T <= 65.00\n",
"| | | | | |--- T <= 57.50\n",
"| | | | | | |--- value: [2.43]\n",
"| | | | | |--- T > 57.50\n",
"| | | | | | |--- value: [2.16]\n",
"| | | | |--- T > 65.00\n",
"| | | | | |--- value: [1.73]\n",
"| | |--- TiO2 > 0.18\n",
"| | | |--- T <= 65.00\n",
"| | | | |--- T <= 57.50\n",
"| | | | | |--- value: [2.84]\n",
"| | | | |--- T > 57.50\n",
"| | | | | |--- value: [2.54]\n",
"| | | |--- T > 65.00\n",
"| | | | |--- value: [1.91]\n",
"\n"
]
}
],
"source": [
"import pickle\n",
"import pandas as pd\n",
"from sklearn import tree\n",
"\n",
"model = pickle.load(open(\"data/vtree.model.sav\", \"rb\"))\n",
"features = (\n",
" pd.read_csv(\"data/viscosity_train.csv\", sep=\";\", decimal=\",\")\n",
" .drop([\"Viscosity\"], 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": 2,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"35"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"[if (T > 32.5) and (T > 47.5) and (TiO2 <= 0.175) and (Al2O3 <= 0.175) and (T > 52.5) and (T > 65.0) and (TiO2 <= 0.025) -> 1.194,\n",
" if (T > 32.5) and (T > 47.5) and (TiO2 <= 0.175) and (Al2O3 <= 0.175) and (T > 52.5) and (T > 65.0) and (TiO2 > 0.025) -> 1.289,\n",
" if (T > 32.5) and (T > 47.5) and (TiO2 <= 0.175) and (Al2O3 <= 0.175) and (T > 52.5) and (T <= 65.0) and (TiO2 <= 0.025) -> 1.548,\n",
" if (T > 32.5) and (T > 47.5) and (TiO2 <= 0.175) and (Al2O3 <= 0.175) and (T <= 52.5) and (TiO2 <= 0.025) and (Al2O3 <= 0.025) -> 1.629,\n",
" if (T > 32.5) and (T > 47.5) and (TiO2 <= 0.175) and (Al2O3 <= 0.175) and (T > 52.5) and (T <= 65.0) and (TiO2 > 0.025) -> 1.662,\n",
" if (T > 32.5) and (T > 47.5) and (TiO2 <= 0.175) and (Al2O3 > 0.175) and (T > 65.0) -> 1.728,\n",
" if (T > 32.5) and (T <= 47.5) and (TiO2 <= 0.175) and (Al2O3 <= 0.175) and (T > 42.5) and (TiO2 <= 0.025) -> 1.832,\n",
" if (T > 32.5) and (T > 47.5) and (TiO2 <= 0.175) and (Al2O3 <= 0.175) and (T <= 52.5) and (TiO2 <= 0.025) and (Al2O3 > 0.025) -> 1.897,\n",
" if (T > 32.5) and (T > 47.5) and (TiO2 > 0.175) and (T > 65.0) -> 1.91,\n",
" if (T > 32.5) and (T > 47.5) and (TiO2 <= 0.175) and (Al2O3 <= 0.175) and (T <= 52.5) and (TiO2 > 0.025) -> 2.109,\n",
" if (T > 32.5) and (T > 47.5) and (TiO2 <= 0.175) and (Al2O3 > 0.175) and (T <= 65.0) and (T > 57.5) -> 2.16,\n",
" if (T > 32.5) and (T <= 47.5) and (TiO2 <= 0.175) and (Al2O3 <= 0.175) and (T <= 42.5) and (TiO2 <= 0.025) and (Al2O3 <= 0.025) -> 2.361,\n",
" if (T > 32.5) and (T <= 47.5) and (TiO2 <= 0.175) and (Al2O3 <= 0.175) and (T > 42.5) and (TiO2 > 0.025) -> 2.402,\n",
" if (T > 32.5) and (T > 47.5) and (TiO2 <= 0.175) and (Al2O3 > 0.175) and (T <= 65.0) and (T <= 57.5) -> 2.426,\n",
" if (T > 32.5) and (T > 47.5) and (TiO2 > 0.175) and (T <= 65.0) and (T > 57.5) -> 2.538,\n",
" if (T > 32.5) and (T <= 47.5) and (TiO2 <= 0.175) and (Al2O3 <= 0.175) and (T <= 42.5) and (TiO2 > 0.025) and (T > 37.5) -> 2.655,\n",
" if (T > 32.5) and (T <= 47.5) and (TiO2 <= 0.175) and (Al2O3 <= 0.175) and (T <= 42.5) and (TiO2 <= 0.025) and (Al2O3 > 0.025) -> 2.682,\n",
" if (T > 32.5) and (T > 47.5) and (TiO2 > 0.175) and (T <= 65.0) and (T <= 57.5) -> 2.838,\n",
" if (T > 32.5) and (T <= 47.5) and (TiO2 <= 0.175) and (Al2O3 <= 0.175) and (T <= 42.5) and (TiO2 > 0.025) and (T <= 37.5) -> 3.121,\n",
" if (T <= 32.5) and (TiO2 <= 0.175) and (Al2O3 <= 0.175) and (T > 22.5) and (TiO2 <= 0.025) and (Al2O3 <= 0.025) -> 3.18,\n",
" if (T <= 32.5) and (TiO2 <= 0.175) and (Al2O3 <= 0.175) and (T > 22.5) and (TiO2 <= 0.025) and (Al2O3 > 0.025) -> 3.38,\n",
" if (T > 32.5) and (T <= 47.5) and (TiO2 > 0.175) and (T > 40.0) -> 3.561,\n",
" if (T > 32.5) and (T <= 47.5) and (TiO2 <= 0.175) and (Al2O3 > 0.175) and (T > 37.5) -> 3.565,\n",
" if (T <= 32.5) and (TiO2 <= 0.175) and (Al2O3 <= 0.175) and (T <= 22.5) and (TiO2 <= 0.025) and (Al2O3 <= 0.025) -> 3.707,\n",
" if (T > 32.5) and (T <= 47.5) and (TiO2 <= 0.175) and (Al2O3 > 0.175) and (T <= 37.5) -> 4.118,\n",
" if (T <= 32.5) and (TiO2 <= 0.175) and (Al2O3 <= 0.175) and (T > 22.5) and (TiO2 > 0.025) -> 4.236,\n",
" if (T > 32.5) and (T <= 47.5) and (TiO2 > 0.175) and (T <= 40.0) -> 4.354,\n",
" if (T <= 32.5) and (TiO2 <= 0.175) and (Al2O3 <= 0.175) and (T <= 22.5) and (TiO2 <= 0.025) and (Al2O3 > 0.025) -> 4.66,\n",
" if (T <= 32.5) and (TiO2 <= 0.175) and (Al2O3 > 0.175) and (T > 22.5) and (T > 27.5) -> 4.731,\n",
" if (T <= 32.5) and (TiO2 <= 0.175) and (Al2O3 <= 0.175) and (T <= 22.5) and (TiO2 > 0.025) -> 4.885,\n",
" if (T <= 32.5) and (TiO2 > 0.175) and (T > 22.5) and (T > 27.5) -> 4.944,\n",
" if (T <= 32.5) and (TiO2 <= 0.175) and (Al2O3 > 0.175) and (T > 22.5) and (T <= 27.5) -> 5.594,\n",
" if (T <= 32.5) and (TiO2 > 0.175) and (T > 22.5) and (T <= 27.5) -> 5.865,\n",
" if (T <= 32.5) and (TiO2 <= 0.175) and (Al2O3 > 0.175) and (T <= 22.5) -> 6.67,\n",
" if (T <= 32.5) and (TiO2 > 0.175) and (T <= 22.5) -> 7.132]"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from src.rules import get_rules\n",
"\n",
"\n",
"rules = get_rules(model, features)\n",
"display(len(rules))\n",
"rules"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"35"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"[if (T > 32.5) and (TiO2 <= 0.175) and (Al2O3 <= 0.175) -> 1.194,\n",
" if (T > 32.5) and (TiO2 <= 0.175) and (TiO2 > 0.025) and (Al2O3 <= 0.175) -> 1.289,\n",
" if (T > 32.5) and (T <= 65.0) and (TiO2 <= 0.175) and (Al2O3 <= 0.175) -> 1.548,\n",
" if (T > 32.5) and (T <= 52.5) and (TiO2 <= 0.175) and (Al2O3 <= 0.175) -> 1.629,\n",
" if (T > 32.5) and (T <= 65.0) and (TiO2 <= 0.175) and (TiO2 > 0.025) and (Al2O3 <= 0.175) -> 1.662,\n",
" if (T > 32.5) and (TiO2 <= 0.175) and (Al2O3 > 0.175) -> 1.728,\n",
" if (T > 32.5) and (T <= 47.5) and (TiO2 <= 0.175) and (Al2O3 <= 0.175) -> 1.832,\n",
" if (T > 32.5) and (T <= 52.5) and (TiO2 <= 0.175) and (Al2O3 <= 0.175) and (Al2O3 > 0.025) -> 1.897,\n",
" if (T > 32.5) and (TiO2 > 0.175) -> 1.91,\n",
" if (T > 32.5) and (T <= 52.5) and (TiO2 <= 0.175) and (TiO2 > 0.025) and (Al2O3 <= 0.175) -> 2.109,\n",
" if (T > 32.5) and (T <= 65.0) and (TiO2 <= 0.175) and (Al2O3 > 0.175) -> 2.16,\n",
" if (T > 32.5) and (T <= 47.5) and (TiO2 <= 0.175) and (Al2O3 <= 0.175) -> 2.361,\n",
" if (T > 32.5) and (T <= 47.5) and (TiO2 <= 0.175) and (TiO2 > 0.025) and (Al2O3 <= 0.175) -> 2.402,\n",
" if (T > 32.5) and (T <= 65.0) and (TiO2 <= 0.175) and (Al2O3 > 0.175) -> 2.426,\n",
" if (T > 32.5) and (T <= 65.0) and (TiO2 > 0.175) -> 2.538,\n",
" if (T > 32.5) and (T <= 47.5) and (TiO2 <= 0.175) and (TiO2 > 0.025) and (Al2O3 <= 0.175) -> 2.655,\n",
" if (T > 32.5) and (T <= 47.5) and (TiO2 <= 0.175) and (Al2O3 <= 0.175) and (Al2O3 > 0.025) -> 2.682,\n",
" if (T > 32.5) and (T <= 65.0) and (TiO2 > 0.175) -> 2.838,\n",
" if (T > 32.5) and (T <= 47.5) and (TiO2 <= 0.175) and (TiO2 > 0.025) and (Al2O3 <= 0.175) -> 3.121,\n",
" if (T <= 32.5) and (T > 22.5) and (TiO2 <= 0.175) and (Al2O3 <= 0.175) -> 3.18,\n",
" if (T <= 32.5) and (T > 22.5) and (TiO2 <= 0.175) and (Al2O3 <= 0.175) and (Al2O3 > 0.025) -> 3.38,\n",
" if (T > 32.5) and (T <= 47.5) and (TiO2 > 0.175) -> 3.561,\n",
" if (T > 32.5) and (T <= 47.5) and (TiO2 <= 0.175) and (Al2O3 > 0.175) -> 3.565,\n",
" if (T <= 32.5) and (TiO2 <= 0.175) and (Al2O3 <= 0.175) -> 3.707,\n",
" if (T > 32.5) and (T <= 47.5) and (TiO2 <= 0.175) and (Al2O3 > 0.175) -> 4.118,\n",
" if (T <= 32.5) and (T > 22.5) and (TiO2 <= 0.175) and (TiO2 > 0.025) and (Al2O3 <= 0.175) -> 4.236,\n",
" if (T > 32.5) and (T <= 47.5) and (TiO2 > 0.175) -> 4.354,\n",
" if (T <= 32.5) and (TiO2 <= 0.175) and (Al2O3 <= 0.175) and (Al2O3 > 0.025) -> 4.66,\n",
" if (T <= 32.5) and (T > 22.5) and (TiO2 <= 0.175) and (Al2O3 > 0.175) -> 4.731,\n",
" if (T <= 32.5) and (TiO2 <= 0.175) and (TiO2 > 0.025) and (Al2O3 <= 0.175) -> 4.885,\n",
" if (T <= 32.5) and (T > 22.5) and (TiO2 > 0.175) -> 4.944,\n",
" if (T <= 32.5) and (T > 22.5) and (TiO2 <= 0.175) and (Al2O3 > 0.175) -> 5.594,\n",
" if (T <= 32.5) and (T > 22.5) and (TiO2 > 0.175) -> 5.865,\n",
" if (T <= 32.5) and (TiO2 <= 0.175) and (Al2O3 > 0.175) -> 6.67,\n",
" if (T <= 32.5) and (TiO2 > 0.175) -> 7.132]"
]
},
"execution_count": 3,
"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": 4,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"26"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"[if (T > 32.5) and (TiO2 <= 0.175) and (Al2O3 <= 0.175) -> 1.194,\n",
" if (T > 32.5) and (TiO2 <= 0.175) and (TiO2 > 0.025) and (Al2O3 <= 0.175) -> 1.289,\n",
" if (T > 32.5) and (T <= 65.0) and (TiO2 <= 0.175) and (Al2O3 <= 0.175) -> 1.548,\n",
" if (T > 32.5) and (T <= 52.5) and (TiO2 <= 0.175) and (Al2O3 <= 0.175) -> 1.629,\n",
" if (T > 32.5) and (T <= 65.0) and (TiO2 <= 0.175) and (TiO2 > 0.025) and (Al2O3 <= 0.175) -> 1.662,\n",
" if (T > 32.5) and (TiO2 <= 0.175) and (Al2O3 > 0.175) -> 1.728,\n",
" if (T > 32.5) and (T <= 52.5) and (TiO2 <= 0.175) and (Al2O3 <= 0.175) and (Al2O3 > 0.025) -> 1.897,\n",
" if (T > 32.5) and (TiO2 > 0.175) -> 1.91,\n",
" if (T > 32.5) and (T <= 52.5) and (TiO2 <= 0.175) and (TiO2 > 0.025) and (Al2O3 <= 0.175) -> 2.109,\n",
" if (T > 32.5) and (T <= 47.5) and (TiO2 <= 0.175) and (Al2O3 <= 0.175) -> 2.097,\n",
" if (T > 32.5) and (T <= 65.0) and (TiO2 <= 0.175) and (Al2O3 > 0.175) -> 2.293,\n",
" if (T > 32.5) and (T <= 47.5) and (TiO2 <= 0.175) and (Al2O3 <= 0.175) and (Al2O3 > 0.025) -> 2.682,\n",
" if (T > 32.5) and (T <= 65.0) and (TiO2 > 0.175) -> 2.688,\n",
" if (T > 32.5) and (T <= 47.5) and (TiO2 <= 0.175) and (TiO2 > 0.025) and (Al2O3 <= 0.175) -> 2.726,\n",
" if (T <= 32.5) and (T > 22.5) and (TiO2 <= 0.175) and (Al2O3 <= 0.175) -> 3.18,\n",
" if (T <= 32.5) and (T > 22.5) and (TiO2 <= 0.175) and (Al2O3 <= 0.175) and (Al2O3 > 0.025) -> 3.38,\n",
" if (T <= 32.5) and (TiO2 <= 0.175) and (Al2O3 <= 0.175) -> 3.707,\n",
" if (T > 32.5) and (T <= 47.5) and (TiO2 <= 0.175) and (Al2O3 > 0.175) -> 3.842,\n",
" if (T <= 32.5) and (T > 22.5) and (TiO2 <= 0.175) and (TiO2 > 0.025) and (Al2O3 <= 0.175) -> 4.236,\n",
" if (T > 32.5) and (T <= 47.5) and (TiO2 > 0.175) -> 3.958,\n",
" if (T <= 32.5) and (TiO2 <= 0.175) and (Al2O3 <= 0.175) and (Al2O3 > 0.025) -> 4.66,\n",
" if (T <= 32.5) and (TiO2 <= 0.175) and (TiO2 > 0.025) and (Al2O3 <= 0.175) -> 4.885,\n",
" if (T <= 32.5) and (T > 22.5) and (TiO2 <= 0.175) and (Al2O3 > 0.175) -> 5.162,\n",
" if (T <= 32.5) and (T > 22.5) and (TiO2 > 0.175) -> 5.405,\n",
" if (T <= 32.5) and (TiO2 <= 0.175) and (Al2O3 > 0.175) -> 6.67,\n",
" if (T <= 32.5) and (TiO2 > 0.175) -> 7.132]"
]
},
"execution_count": 4,
"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": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['(Al2O3 <= 0.175)', '(Al2O3 > 0.025)', '(Al2O3 > 0.175)', '(TiO2 <= 0.175)', '(TiO2 > 0.025)', '(TiO2 > 0.175)']\n"
]
},
{
"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>(Al2O3 &lt;= 0.175)</th>\n",
" <th>(Al2O3 &gt; 0.025)</th>\n",
" <th>(Al2O3 &gt; 0.175)</th>\n",
" <th>(TiO2 &lt;= 0.175)</th>\n",
" <th>(TiO2 &gt; 0.025)</th>\n",
" <th>(TiO2 &gt; 0.175)</th>\n",
" <th>consequent</th>\n",
" </tr>\n",
" <tr>\n",
" <th>rule</th>\n",
" <th></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>if (T &gt; 32.5) and (TiO2 &lt;= 0.175) and (Al2O3 &lt;= 0.175) -&gt; 1.194</th>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1.194</td>\n",
" </tr>\n",
" <tr>\n",
" <th>if (T &gt; 32.5) and (TiO2 &lt;= 0.175) and (TiO2 &gt; 0.025) and (Al2O3 &lt;= 0.175) -&gt; 1.289</th>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1.289</td>\n",
" </tr>\n",
" <tr>\n",
" <th>if (T &gt; 32.5) and (T &lt;= 65.0) and (TiO2 &lt;= 0.175) and (Al2O3 &lt;= 0.175) -&gt; 1.548</th>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1.548</td>\n",
" </tr>\n",
" <tr>\n",
" <th>if (T &gt; 32.5) and (T &lt;= 52.5) and (TiO2 &lt;= 0.175) and (Al2O3 &lt;= 0.175) -&gt; 1.629</th>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1.629</td>\n",
" </tr>\n",
" <tr>\n",
" <th>if (T &gt; 32.5) and (T &lt;= 65.0) and (TiO2 &lt;= 0.175) and (TiO2 &gt; 0.025) and (Al2O3 &lt;= 0.175) -&gt; 1.662</th>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1.662</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" (Al2O3 <= 0.175) \\\n",
"rule \n",
"if (T > 32.5) and (TiO2 <= 0.175) and (Al2O3 <=... 1 \n",
"if (T > 32.5) and (TiO2 <= 0.175) and (TiO2 > 0... 1 \n",
"if (T > 32.5) and (T <= 65.0) and (TiO2 <= 0.17... 1 \n",
"if (T > 32.5) and (T <= 52.5) and (TiO2 <= 0.17... 1 \n",
"if (T > 32.5) and (T <= 65.0) and (TiO2 <= 0.17... 1 \n",
"\n",
" (Al2O3 > 0.025) \\\n",
"rule \n",
"if (T > 32.5) and (TiO2 <= 0.175) and (Al2O3 <=... 0 \n",
"if (T > 32.5) and (TiO2 <= 0.175) and (TiO2 > 0... 0 \n",
"if (T > 32.5) and (T <= 65.0) and (TiO2 <= 0.17... 0 \n",
"if (T > 32.5) and (T <= 52.5) and (TiO2 <= 0.17... 0 \n",
"if (T > 32.5) and (T <= 65.0) and (TiO2 <= 0.17... 0 \n",
"\n",
" (Al2O3 > 0.175) \\\n",
"rule \n",
"if (T > 32.5) and (TiO2 <= 0.175) and (Al2O3 <=... 0 \n",
"if (T > 32.5) and (TiO2 <= 0.175) and (TiO2 > 0... 0 \n",
"if (T > 32.5) and (T <= 65.0) and (TiO2 <= 0.17... 0 \n",
"if (T > 32.5) and (T <= 52.5) and (TiO2 <= 0.17... 0 \n",
"if (T > 32.5) and (T <= 65.0) and (TiO2 <= 0.17... 0 \n",
"\n",
" (TiO2 <= 0.175) \\\n",
"rule \n",
"if (T > 32.5) and (TiO2 <= 0.175) and (Al2O3 <=... 1 \n",
"if (T > 32.5) and (TiO2 <= 0.175) and (TiO2 > 0... 1 \n",
"if (T > 32.5) and (T <= 65.0) and (TiO2 <= 0.17... 1 \n",
"if (T > 32.5) and (T <= 52.5) and (TiO2 <= 0.17... 1 \n",
"if (T > 32.5) and (T <= 65.0) and (TiO2 <= 0.17... 1 \n",
"\n",
" (TiO2 > 0.025) \\\n",
"rule \n",
"if (T > 32.5) and (TiO2 <= 0.175) and (Al2O3 <=... 0 \n",
"if (T > 32.5) and (TiO2 <= 0.175) and (TiO2 > 0... 1 \n",
"if (T > 32.5) and (T <= 65.0) and (TiO2 <= 0.17... 0 \n",
"if (T > 32.5) and (T <= 52.5) and (TiO2 <= 0.17... 0 \n",
"if (T > 32.5) and (T <= 65.0) and (TiO2 <= 0.17... 1 \n",
"\n",
" (TiO2 > 0.175) consequent \n",
"rule \n",
"if (T > 32.5) and (TiO2 <= 0.175) and (Al2O3 <=... 0 1.194 \n",
"if (T > 32.5) and (TiO2 <= 0.175) and (TiO2 > 0... 0 1.289 \n",
"if (T > 32.5) and (T <= 65.0) and (TiO2 <= 0.17... 0 1.548 \n",
"if (T > 32.5) and (T <= 52.5) and (TiO2 <= 0.17... 0 1.629 \n",
"if (T > 32.5) and (T <= 65.0) and (TiO2 <= 0.17... 0 1.662 "
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from src.rules import get_features, vectorize_rules\n",
"\n",
"features = get_features(rules, [\"T\"])\n",
"print(features)\n",
"\n",
"df_rules = vectorize_rules(rules, features)\n",
"df_rules.head(5)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"c:\\Users\\user\\Projects\\python\\fuzzy\\.venv\\Lib\\site-packages\\sklearn\\base.py:1473: ConvergenceWarning: Number of distinct clusters (5) found smaller than n_clusters (6). Possibly due to duplicate points in X.\n",
" return fit_method(estimator, *args, **kwargs)\n"
]
},
{
"data": {
"text/plain": [
"{2: 0.42601604060235754,\n",
" 3: 0.7018993361356377,\n",
" 4: 0.8249121250065079,\n",
" 5: 1.0,\n",
Fix max_clusters calculation
2024-11-15 10:58:51 +04:00
" 6: 1.0}"
initial
2024-11-01 11:04:05 +04:00
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
Fix max_clusters calculation
2024-11-15 10:58:51 +04:00
"image/png": "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
initial
2024-11-01 11:04:05 +04:00
"text/plain": [
"<Figure size 400x400 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"'The best clusters count is 5'"
]
},
"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": 7,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Кластер 1 (6):\n",
"if (T > 32.5) and (TiO2 <= 0.175) and (Al2O3 <= 0.175) -> 1.194;\n",
"if (T > 32.5) and (T <= 65.0) and (TiO2 <= 0.175) and (Al2O3 <= 0.175) -> 1.548;\n",
"if (T > 32.5) and (T <= 52.5) and (TiO2 <= 0.175) and (Al2O3 <= 0.175) -> 1.629;\n",
"if (T > 32.5) and (T <= 47.5) and (TiO2 <= 0.175) and (Al2O3 <= 0.175) -> 2.097;\n",
"if (T <= 32.5) and (T > 22.5) and (TiO2 <= 0.175) and (Al2O3 <= 0.175) -> 3.18;\n",
"if (T <= 32.5) and (TiO2 <= 0.175) and (Al2O3 <= 0.175) -> 3.707\n",
"--------\n",
"Кластер 2 (5):\n",
"if (T > 32.5) and (TiO2 <= 0.175) and (Al2O3 > 0.175) -> 1.728;\n",
"if (T > 32.5) and (T <= 65.0) and (TiO2 <= 0.175) and (Al2O3 > 0.175) -> 2.293;\n",
"if (T > 32.5) and (T <= 47.5) and (TiO2 <= 0.175) and (Al2O3 > 0.175) -> 3.842;\n",
"if (T <= 32.5) and (T > 22.5) and (TiO2 <= 0.175) and (Al2O3 > 0.175) -> 5.162;\n",
"if (T <= 32.5) and (TiO2 <= 0.175) and (Al2O3 > 0.175) -> 6.67\n",
"--------\n",
"Кластер 3 (5):\n",
"if (T > 32.5) and (TiO2 > 0.175) -> 1.91;\n",
"if (T > 32.5) and (T <= 65.0) and (TiO2 > 0.175) -> 2.688;\n",
"if (T > 32.5) and (T <= 47.5) and (TiO2 > 0.175) -> 3.958;\n",
"if (T <= 32.5) and (T > 22.5) and (TiO2 > 0.175) -> 5.405;\n",
"if (T <= 32.5) and (TiO2 > 0.175) -> 7.132\n",
"--------\n",
"Кластер 4 (6):\n",
"if (T > 32.5) and (TiO2 <= 0.175) and (TiO2 > 0.025) and (Al2O3 <= 0.175) -> 1.289;\n",
"if (T > 32.5) and (T <= 65.0) and (TiO2 <= 0.175) and (TiO2 > 0.025) and (Al2O3 <= 0.175) -> 1.662;\n",
"if (T > 32.5) and (T <= 52.5) and (TiO2 <= 0.175) and (TiO2 > 0.025) and (Al2O3 <= 0.175) -> 2.109;\n",
"if (T > 32.5) and (T <= 47.5) and (TiO2 <= 0.175) and (TiO2 > 0.025) and (Al2O3 <= 0.175) -> 2.726;\n",
"if (T <= 32.5) and (T > 22.5) and (TiO2 <= 0.175) and (TiO2 > 0.025) and (Al2O3 <= 0.175) -> 4.236;\n",
"if (T <= 32.5) and (TiO2 <= 0.175) and (TiO2 > 0.025) and (Al2O3 <= 0.175) -> 4.885\n",
"--------\n",
"Кластер 5 (4):\n",
"if (T > 32.5) and (T <= 52.5) and (TiO2 <= 0.175) and (Al2O3 <= 0.175) and (Al2O3 > 0.025) -> 1.897;\n",
"if (T > 32.5) and (T <= 47.5) and (TiO2 <= 0.175) and (Al2O3 <= 0.175) and (Al2O3 > 0.025) -> 2.682;\n",
"if (T <= 32.5) and (T > 22.5) and (TiO2 <= 0.175) and (Al2O3 <= 0.175) and (Al2O3 > 0.025) -> 3.38;\n",
"if (T <= 32.5) and (TiO2 <= 0.175) and (Al2O3 <= 0.175) and (Al2O3 > 0.025) -> 4.66\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": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>T</th>\n",
" <th>Al2O3</th>\n",
" <th>TiO2</th>\n",
" <th>Viscosity</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>20</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>3.707</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>25</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>3.180</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>35</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>2.361</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" T Al2O3 TiO2 Viscosity\n",
"0 20 0.0 0.0 3.707\n",
"1 25 0.0 0.0 3.180\n",
"2 35 0.0 0.0 2.361"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"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>T</th>\n",
" <th>Al2O3</th>\n",
" <th>TiO2</th>\n",
" <th>Viscosity</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>30</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>2.716</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>40</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>2.073</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>60</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>1.329</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" T Al2O3 TiO2 Viscosity\n",
"0 30 0.0 0.0 2.716\n",
"1 40 0.0 0.0 2.073\n",
"2 60 0.0 0.0 1.329"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"viscosity_train = pd.read_csv(\"data/viscosity_train.csv\", sep=\";\", decimal=\",\")\n",
"viscosity_test = pd.read_csv(\"data/viscosity_test.csv\", sep=\";\", decimal=\",\")\n",
"\n",
"display(viscosity_train.head(3))\n",
"display(viscosity_test.head(3))"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[[if (T = 70) and (TiO2 = 0.0) and (Al2O3 = 0.0) -> 1.194,\n",
" if (T = 48.75) and (TiO2 = 0.0) and (Al2O3 = 0.0) -> 1.548,\n",
" if (T = 42.5) and (TiO2 = 0.0) and (Al2O3 = 0.0) -> 1.629,\n",
" if (T = 40.0) and (TiO2 = 0.0) and (Al2O3 = 0.0) -> 2.097,\n",
" if (T = 27.5) and (TiO2 = 0.0) and (Al2O3 = 0.0) -> 3.18,\n",
" if (T = 20) and (TiO2 = 0.0) and (Al2O3 = 0.0) -> 3.707],\n",
" [if (T = 70) and (TiO2 = 0.0) and (Al2O3 = 0.3) -> 1.728,\n",
" if (T = 48.75) and (TiO2 = 0.0) and (Al2O3 = 0.3) -> 2.293,\n",
" if (T = 40.0) and (TiO2 = 0.0) and (Al2O3 = 0.3) -> 3.842,\n",
" if (T = 27.5) and (TiO2 = 0.0) and (Al2O3 = 0.3) -> 5.162,\n",
" if (T = 20) and (TiO2 = 0.0) and (Al2O3 = 0.3) -> 6.67],\n",
" [if (T = 70) and (TiO2 = 0.3) -> 1.91,\n",
" if (T = 48.75) and (TiO2 = 0.3) -> 2.688,\n",
" if (T = 40.0) and (TiO2 = 0.3) -> 3.958,\n",
" if (T = 27.5) and (TiO2 = 0.3) -> 5.405,\n",
" if (T = 20) and (TiO2 = 0.3) -> 7.132],\n",
" [if (T = 70) and (TiO2 = 0.1) and (Al2O3 = 0.0) -> 1.289,\n",
" if (T = 48.75) and (TiO2 = 0.1) and (Al2O3 = 0.0) -> 1.662,\n",
" if (T = 42.5) and (TiO2 = 0.1) and (Al2O3 = 0.0) -> 2.109,\n",
" if (T = 40.0) and (TiO2 = 0.1) and (Al2O3 = 0.0) -> 2.726,\n",
" if (T = 27.5) and (TiO2 = 0.1) and (Al2O3 = 0.0) -> 4.236,\n",
" if (T = 20) and (TiO2 = 0.1) and (Al2O3 = 0.0) -> 4.885],\n",
" [if (T = 42.5) and (TiO2 = 0.0) and (Al2O3 = 0.1) -> 1.897,\n",
" if (T = 40.0) and (TiO2 = 0.0) and (Al2O3 = 0.1) -> 2.682,\n",
" if (T = 27.5) and (TiO2 = 0.0) and (Al2O3 = 0.1) -> 3.38,\n",
" if (T = 20) and (TiO2 = 0.0) and (Al2O3 = 0.1) -> 4.66]]"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from src.rules import simplify_and_group_rules\n",
"\n",
"clustered_rules = simplify_and_group_rules(\n",
" viscosity_train, rules, clusters_num, kmeans.labels_\n",
")\n",
"clustered_rules"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"c:\\Users\\user\\Projects\\python\\fuzzy\\.venv\\Lib\\site-packages\\skfuzzy\\control\\fuzzyvariable.py:125: UserWarning: FigureCanvasAgg is non-interactive, and thus cannot be shown\n",
" fig.show()\n"
]
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import numpy as np\n",
"from skfuzzy import control as ctrl\n",
"import skfuzzy as fuzz\n",
"\n",
"temp = ctrl.Antecedent(viscosity_train[\"T\"].sort_values().unique(), \"temp\")\n",
"al = ctrl.Antecedent(np.arange(0, 0.3, 0.005), \"al\")\n",
"ti = ctrl.Antecedent(np.arange(0, 0.3, 0.005), \"ti\")\n",
"viscosity = ctrl.Consequent(np.arange(1.18, 3.71, 0.00001), \"viscosity\")\n",
"\n",
"temp.automf(5, variable_type=\"quant\")\n",
"temp.view()\n",
"al.automf(3, variable_type=\"quant\")\n",
"al.view()\n",
"ti.automf(3, variable_type=\"quant\")\n",
"ti.view()\n",
"viscosity.automf(5, variable_type=\"quant\")\n",
"viscosity.view()"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"19"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"[IF (temp[higher] AND ti[low]) AND al[low] THEN viscosity[lower]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF (temp[average] AND ti[low]) AND al[low] THEN viscosity[low]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF (temp[low] AND ti[low]) AND al[low] THEN viscosity[high]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF (temp[lower] AND ti[low]) AND al[low] THEN viscosity[higher]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF (temp[higher] AND ti[low]) AND al[high] THEN viscosity[low]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF (temp[average] AND ti[low]) AND al[high] THEN viscosity[higher]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF (temp[low] AND ti[low]) AND al[high] THEN viscosity[higher]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF (temp[lower] AND ti[low]) AND al[high] THEN viscosity[higher]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF temp[higher] AND ti[high] THEN viscosity[low]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF temp[average] AND ti[high] THEN viscosity[higher]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF temp[low] AND ti[high] THEN viscosity[higher]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF temp[lower] AND ti[high] THEN viscosity[higher]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF (temp[higher] AND ti[average]) AND al[low] THEN viscosity[lower]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF (temp[average] AND ti[average]) AND al[low] THEN viscosity[average]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF (temp[low] AND ti[average]) AND al[low] THEN viscosity[higher]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF (temp[lower] AND ti[average]) AND al[low] THEN viscosity[higher]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF (temp[average] AND ti[low]) AND al[average] THEN viscosity[average]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF (temp[low] AND ti[low]) AND al[average] THEN viscosity[high]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax,\n",
" IF (temp[lower] AND ti[low]) AND al[average] THEN viscosity[higher]\n",
" \tAND aggregation function : fmin\n",
" \tOR aggregation function : fmax]"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from src.rules import get_fuzzy_rules\n",
"\n",
"fuzzy_variables = {\"Al2O3\": al, \"TiO2\": ti, \"T\": temp, \"consequent\": viscosity}\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": 12,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"=============\n",
" Antecedents \n",
"=============\n",
"Antecedent: temp = 20\n",
" - lower : 1.0\n",
" - low : 0.0\n",
" - average : 0.0\n",
" - high : 0.0\n",
" - higher : 0.0\n",
"Antecedent: ti = 0.0\n",
" - low : 1.0\n",
" - average : 0.0\n",
" - high : 0.0\n",
"Antecedent: al = 0.0\n",
" - low : 1.0\n",
" - average : 0.0\n",
" - high : 0.0\n",
"\n",
"=======\n",
" Rules \n",
"=======\n",
"RULE #0:\n",
" IF (temp[higher] AND ti[low]) AND al[low] THEN viscosity[lower]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - temp[higher] : 0.0\n",
" - ti[low] : 1.0\n",
" - al[low] : 1.0\n",
" (temp[higher] AND ti[low]) AND al[low] = 0.0\n",
" Activation (THEN-clause):\n",
" viscosity[lower] : 0.0\n",
"\n",
"RULE #1:\n",
" IF (temp[average] AND ti[low]) AND al[low] THEN viscosity[low]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - temp[average] : 0.0\n",
" - ti[low] : 1.0\n",
" - al[low] : 1.0\n",
" (temp[average] AND ti[low]) AND al[low] = 0.0\n",
" Activation (THEN-clause):\n",
" viscosity[low] : 0.0\n",
"\n",
"RULE #2:\n",
" IF (temp[low] AND ti[low]) AND al[low] THEN viscosity[high]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - temp[low] : 0.0\n",
" - ti[low] : 1.0\n",
" - al[low] : 1.0\n",
" (temp[low] AND ti[low]) AND al[low] = 0.0\n",
" Activation (THEN-clause):\n",
" viscosity[high] : 0.0\n",
"\n",
"RULE #3:\n",
" IF (temp[lower] AND ti[low]) AND al[low] THEN viscosity[higher]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - temp[lower] : 1.0\n",
" - ti[low] : 1.0\n",
" - al[low] : 1.0\n",
" (temp[lower] AND ti[low]) AND al[low] = 1.0\n",
" Activation (THEN-clause):\n",
" viscosity[higher] : 1.0\n",
"\n",
"RULE #4:\n",
" IF (temp[higher] AND ti[low]) AND al[high] THEN viscosity[low]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - temp[higher] : 0.0\n",
" - ti[low] : 1.0\n",
" - al[high] : 0.0\n",
" (temp[higher] AND ti[low]) AND al[high] = 0.0\n",
" Activation (THEN-clause):\n",
" viscosity[low] : 0.0\n",
"\n",
"RULE #5:\n",
" IF (temp[average] AND ti[low]) AND al[high] THEN viscosity[higher]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - temp[average] : 0.0\n",
" - ti[low] : 1.0\n",
" - al[high] : 0.0\n",
" (temp[average] AND ti[low]) AND al[high] = 0.0\n",
" Activation (THEN-clause):\n",
" viscosity[higher] : 0.0\n",
"\n",
"RULE #6:\n",
" IF (temp[low] AND ti[low]) AND al[high] THEN viscosity[higher]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - temp[low] : 0.0\n",
" - ti[low] : 1.0\n",
" - al[high] : 0.0\n",
" (temp[low] AND ti[low]) AND al[high] = 0.0\n",
" Activation (THEN-clause):\n",
" viscosity[higher] : 0.0\n",
"\n",
"RULE #7:\n",
" IF (temp[lower] AND ti[low]) AND al[high] THEN viscosity[higher]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - temp[lower] : 1.0\n",
" - ti[low] : 1.0\n",
" - al[high] : 0.0\n",
" (temp[lower] AND ti[low]) AND al[high] = 0.0\n",
" Activation (THEN-clause):\n",
" viscosity[higher] : 0.0\n",
"\n",
"RULE #8:\n",
" IF temp[higher] AND ti[high] THEN viscosity[low]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - temp[higher] : 0.0\n",
" - ti[high] : 0.0\n",
" temp[higher] AND ti[high] = 0.0\n",
" Activation (THEN-clause):\n",
" viscosity[low] : 0.0\n",
"\n",
"RULE #9:\n",
" IF temp[average] AND ti[high] THEN viscosity[higher]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - temp[average] : 0.0\n",
" - ti[high] : 0.0\n",
" temp[average] AND ti[high] = 0.0\n",
" Activation (THEN-clause):\n",
" viscosity[higher] : 0.0\n",
"\n",
"RULE #10:\n",
" IF temp[low] AND ti[high] THEN viscosity[higher]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - temp[low] : 0.0\n",
" - ti[high] : 0.0\n",
" temp[low] AND ti[high] = 0.0\n",
" Activation (THEN-clause):\n",
" viscosity[higher] : 0.0\n",
"\n",
"RULE #11:\n",
" IF temp[lower] AND ti[high] THEN viscosity[higher]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - temp[lower] : 1.0\n",
" - ti[high] : 0.0\n",
" temp[lower] AND ti[high] = 0.0\n",
" Activation (THEN-clause):\n",
" viscosity[higher] : 0.0\n",
"\n",
"RULE #12:\n",
" IF (temp[higher] AND ti[average]) AND al[low] THEN viscosity[lower]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - temp[higher] : 0.0\n",
" - ti[average] : 0.0\n",
" - al[low] : 1.0\n",
" (temp[higher] AND ti[average]) AND al[low] = 0.0\n",
" Activation (THEN-clause):\n",
" viscosity[lower] : 0.0\n",
"\n",
"RULE #13:\n",
" IF (temp[average] AND ti[average]) AND al[low] THEN viscosity[average]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - temp[average] : 0.0\n",
" - ti[average] : 0.0\n",
" - al[low] : 1.0\n",
" (temp[average] AND ti[average]) AND al[low] = 0.0\n",
" Activation (THEN-clause):\n",
" viscosity[average] : 0.0\n",
"\n",
"RULE #14:\n",
" IF (temp[low] AND ti[average]) AND al[low] THEN viscosity[higher]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - temp[low] : 0.0\n",
" - ti[average] : 0.0\n",
" - al[low] : 1.0\n",
" (temp[low] AND ti[average]) AND al[low] = 0.0\n",
" Activation (THEN-clause):\n",
" viscosity[higher] : 0.0\n",
"\n",
"RULE #15:\n",
" IF (temp[lower] AND ti[average]) AND al[low] THEN viscosity[higher]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - temp[lower] : 1.0\n",
" - ti[average] : 0.0\n",
" - al[low] : 1.0\n",
" (temp[lower] AND ti[average]) AND al[low] = 0.0\n",
" Activation (THEN-clause):\n",
" viscosity[higher] : 0.0\n",
"\n",
"RULE #16:\n",
" IF (temp[average] AND ti[low]) AND al[average] THEN viscosity[average]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - temp[average] : 0.0\n",
" - ti[low] : 1.0\n",
" - al[average] : 0.0\n",
" (temp[average] AND ti[low]) AND al[average] = 0.0\n",
" Activation (THEN-clause):\n",
" viscosity[average] : 0.0\n",
"\n",
"RULE #17:\n",
" IF (temp[low] AND ti[low]) AND al[average] THEN viscosity[high]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - temp[low] : 0.0\n",
" - ti[low] : 1.0\n",
" - al[average] : 0.0\n",
" (temp[low] AND ti[low]) AND al[average] = 0.0\n",
" Activation (THEN-clause):\n",
" viscosity[high] : 0.0\n",
"\n",
"RULE #18:\n",
" IF (temp[lower] AND ti[low]) AND al[average] THEN viscosity[higher]\n",
"\tAND aggregation function : fmin\n",
"\tOR aggregation function : fmax\n",
"\n",
" Aggregation (IF-clause):\n",
" - temp[lower] : 1.0\n",
" - ti[low] : 1.0\n",
" - al[average] : 0.0\n",
" (temp[lower] AND ti[low]) AND al[average] = 0.0\n",
" Activation (THEN-clause):\n",
" viscosity[higher] : 0.0\n",
"\n",
"\n",
"==============================\n",
" Intermediaries and Conquests \n",
"==============================\n",
"Consequent: viscosity = 3.499157499995422\n",
" lower:\n",
" Accumulate using accumulation_max : 0.0\n",
" low:\n",
" Accumulate using accumulation_max : 0.0\n",
" average:\n",
" Accumulate using accumulation_max : 0.0\n",
" high:\n",
" Accumulate using accumulation_max : 0.0\n",
" higher:\n",
" Accumulate using accumulation_max : 1.0\n",
"\n"
]
},
{
"data": {
"text/plain": [
"np.float64(3.499157499995422)"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sim.input[\"temp\"] = 20\n",
"sim.input[\"al\"] = 0.0\n",
"sim.input[\"ti\"] = 0.0\n",
"sim.compute()\n",
"sim.print_state()\n",
"display(sim.output[\"viscosity\"])"
]
},
{
"cell_type": "code",
"execution_count": 13,
"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>T</th>\n",
" <th>Al2O3</th>\n",
" <th>TiO2</th>\n",
" <th>Viscosity</th>\n",
" <th>ViscosityPred</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>20</td>\n",
" <td>0.00</td>\n",
" <td>0.0</td>\n",
" <td>3.707</td>\n",
" <td>3.499157</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>25</td>\n",
" <td>0.00</td>\n",
" <td>0.0</td>\n",
" <td>3.180</td>\n",
" <td>3.188565</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>35</td>\n",
" <td>0.00</td>\n",
" <td>0.0</td>\n",
" <td>2.361</td>\n",
" <td>2.732494</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>45</td>\n",
" <td>0.00</td>\n",
" <td>0.0</td>\n",
" <td>1.832</td>\n",
" <td>1.812498</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>50</td>\n",
" <td>0.00</td>\n",
" <td>0.0</td>\n",
" <td>1.629</td>\n",
" <td>1.812498</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>55</td>\n",
" <td>0.00</td>\n",
" <td>0.0</td>\n",
" <td>1.465</td>\n",
" <td>1.812498</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>70</td>\n",
" <td>0.00</td>\n",
" <td>0.0</td>\n",
" <td>1.194</td>\n",
" <td>1.390833</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>20</td>\n",
" <td>0.05</td>\n",
" <td>0.0</td>\n",
" <td>4.660</td>\n",
" <td>3.481064</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>30</td>\n",
" <td>0.05</td>\n",
" <td>0.0</td>\n",
" <td>3.380</td>\n",
" <td>3.090537</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>35</td>\n",
" <td>0.05</td>\n",
" <td>0.0</td>\n",
" <td>2.874</td>\n",
" <td>2.703435</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>40</td>\n",
" <td>0.05</td>\n",
" <td>0.0</td>\n",
" <td>2.489</td>\n",
" <td>2.365680</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>50</td>\n",
" <td>0.05</td>\n",
" <td>0.0</td>\n",
" <td>1.897</td>\n",
" <td>2.054459</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>55</td>\n",
" <td>0.05</td>\n",
" <td>0.0</td>\n",
" <td>1.709</td>\n",
" <td>2.128746</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>60</td>\n",
" <td>0.05</td>\n",
" <td>0.0</td>\n",
" <td>1.470</td>\n",
" <td>1.465795</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>20</td>\n",
" <td>0.30</td>\n",
" <td>0.0</td>\n",
" <td>6.670</td>\n",
" <td>3.499157</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" T Al2O3 TiO2 Viscosity ViscosityPred\n",
"0 20 0.00 0.0 3.707 3.499157\n",
"1 25 0.00 0.0 3.180 3.188565\n",
"2 35 0.00 0.0 2.361 2.732494\n",
"3 45 0.00 0.0 1.832 1.812498\n",
"4 50 0.00 0.0 1.629 1.812498\n",
"5 55 0.00 0.0 1.465 1.812498\n",
"6 70 0.00 0.0 1.194 1.390833\n",
"7 20 0.05 0.0 4.660 3.481064\n",
"8 30 0.05 0.0 3.380 3.090537\n",
"9 35 0.05 0.0 2.874 2.703435\n",
"10 40 0.05 0.0 2.489 2.365680\n",
"11 50 0.05 0.0 1.897 2.054459\n",
"12 55 0.05 0.0 1.709 2.128746\n",
"13 60 0.05 0.0 1.470 1.465795\n",
"14 20 0.30 0.0 6.670 3.499157"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"def fuzzy_pred(row):\n",
" sim.input[\"temp\"] = row[\"T\"]\n",
" sim.input[\"al\"] = row[\"Al2O3\"]\n",
" sim.input[\"ti\"] = row[\"TiO2\"]\n",
" sim.compute()\n",
" return sim.output[\"viscosity\"]\n",
"\n",
"result_train = viscosity_train.copy()\n",
"result_train[\"ViscosityPred\"] = result_train.apply(fuzzy_pred, axis=1)\n",
"result_train.head(15)"
]
},
{
"cell_type": "code",
"execution_count": 14,
"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>T</th>\n",
" <th>Al2O3</th>\n",
" <th>TiO2</th>\n",
" <th>Viscosity</th>\n",
" <th>ViscosityPred</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>30</td>\n",
" <td>0.00</td>\n",
" <td>0.00</td>\n",
" <td>2.716</td>\n",
" <td>3.089540</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>40</td>\n",
" <td>0.00</td>\n",
" <td>0.00</td>\n",
" <td>2.073</td>\n",
" <td>2.359522</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>60</td>\n",
" <td>0.00</td>\n",
" <td>0.00</td>\n",
" <td>1.329</td>\n",
" <td>1.465795</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>65</td>\n",
" <td>0.00</td>\n",
" <td>0.00</td>\n",
" <td>1.211</td>\n",
" <td>1.414928</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>25</td>\n",
" <td>0.05</td>\n",
" <td>0.00</td>\n",
" <td>4.120</td>\n",
" <td>3.188565</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>45</td>\n",
" <td>0.05</td>\n",
" <td>0.00</td>\n",
" <td>2.217</td>\n",
" <td>2.045546</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>65</td>\n",
" <td>0.05</td>\n",
" <td>0.00</td>\n",
" <td>1.315</td>\n",
" <td>1.414928</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>70</td>\n",
" <td>0.05</td>\n",
" <td>0.00</td>\n",
" <td>1.105</td>\n",
" <td>1.408926</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>45</td>\n",
" <td>0.30</td>\n",
" <td>0.00</td>\n",
" <td>3.111</td>\n",
" <td>3.499157</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>50</td>\n",
" <td>0.30</td>\n",
" <td>0.00</td>\n",
" <td>2.735</td>\n",
" <td>3.475062</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>65</td>\n",
" <td>0.30</td>\n",
" <td>0.00</td>\n",
" <td>1.936</td>\n",
" <td>1.812498</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>30</td>\n",
" <td>0.00</td>\n",
" <td>0.05</td>\n",
" <td>3.587</td>\n",
" <td>3.111691</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>55</td>\n",
" <td>0.00</td>\n",
" <td>0.05</td>\n",
" <td>1.953</td>\n",
" <td>2.128746</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>65</td>\n",
" <td>0.00</td>\n",
" <td>0.05</td>\n",
" <td>1.443</td>\n",
" <td>1.414928</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>40</td>\n",
" <td>0.00</td>\n",
" <td>0.30</td>\n",
" <td>3.990</td>\n",
" <td>3.475062</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>50</td>\n",
" <td>0.00</td>\n",
" <td>0.30</td>\n",
" <td>3.189</td>\n",
" <td>3.475062</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>65</td>\n",
" <td>0.00</td>\n",
" <td>0.30</td>\n",
" <td>2.287</td>\n",
" <td>1.812498</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" T Al2O3 TiO2 Viscosity ViscosityPred\n",
"0 30 0.00 0.00 2.716 3.089540\n",
"1 40 0.00 0.00 2.073 2.359522\n",
"2 60 0.00 0.00 1.329 1.465795\n",
"3 65 0.00 0.00 1.211 1.414928\n",
"4 25 0.05 0.00 4.120 3.188565\n",
"5 45 0.05 0.00 2.217 2.045546\n",
"6 65 0.05 0.00 1.315 1.414928\n",
"7 70 0.05 0.00 1.105 1.408926\n",
"8 45 0.30 0.00 3.111 3.499157\n",
"9 50 0.30 0.00 2.735 3.475062\n",
"10 65 0.30 0.00 1.936 1.812498\n",
"11 30 0.00 0.05 3.587 3.111691\n",
"12 55 0.00 0.05 1.953 2.128746\n",
"13 65 0.00 0.05 1.443 1.414928\n",
"14 40 0.00 0.30 3.990 3.475062\n",
"15 50 0.00 0.30 3.189 3.475062\n",
"16 65 0.00 0.30 2.287 1.812498"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"result_test = viscosity_test.copy()\n",
"result_test[\"ViscosityPred\"] = result_test.apply(fuzzy_pred, axis=1)\n",
"result_test"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'RMSE_train': 1.0977710360150494,\n",
" 'RMSE_test': 0.4076186194536602,\n",
" 'RMAE_test': 0.5797504263400755,\n",
" 'R2_test': 0.813200460937507}"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import math\n",
"from sklearn import metrics\n",
"\n",
"\n",
"rmetrics = {}\n",
"rmetrics[\"RMSE_train\"] = math.sqrt(\n",
" metrics.mean_squared_error(result_train[\"Viscosity\"], result_train[\"ViscosityPred\"])\n",
")\n",
"rmetrics[\"RMSE_test\"] = math.sqrt(\n",
" metrics.mean_squared_error(result_test[\"Viscosity\"], result_test[\"ViscosityPred\"])\n",
")\n",
"rmetrics[\"RMAE_test\"] = math.sqrt(\n",
" metrics.mean_absolute_error(result_test[\"Viscosity\"], result_test[\"ViscosityPred\"])\n",
")\n",
"rmetrics[\"R2_test\"] = metrics.r2_score(\n",
" result_test[\"Viscosity\"], result_test[\"ViscosityPred\"]\n",
")\n",
"\n",
"rmetrics"
]
}
],
"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": "3.12.7"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
Reference in New Issue Copy Permalink