fuzzy-rules-generator/density_tree.ipynb at d30c1005e9dc95a04cb3d262ba848287c23e7535

In [1]:

import pickle
import pandas as pd
from sklearn import tree

model = pickle.load(open("data/dtree.model.sav", "rb"))
features = (
    pd.read_csv("data/density_train.csv", sep=";", decimal=",")
    .drop(["Density"], axis=1)
    .columns.values.tolist()
)

rules = tree.export_text(model, feature_names=features)
print(rules)

|--- Al2O3 <= 0.18
|   |--- TiO2 <= 0.18
|   |   |--- T <= 32.50
|   |   |   |--- TiO2 <= 0.03
|   |   |   |   |--- Al2O3 <= 0.03
|   |   |   |   |   |--- T <= 22.50
|   |   |   |   |   |   |--- value: [1.06]
|   |   |   |   |   |--- T >  22.50
|   |   |   |   |   |   |--- value: [1.06]
|   |   |   |   |--- Al2O3 >  0.03
|   |   |   |   |   |--- value: [1.09]
|   |   |   |--- TiO2 >  0.03
|   |   |   |   |--- T <= 27.50
|   |   |   |   |   |--- T <= 22.50
|   |   |   |   |   |   |--- value: [1.09]
|   |   |   |   |   |--- T >  22.50
|   |   |   |   |   |   |--- value: [1.09]
|   |   |   |   |--- T >  27.50
|   |   |   |   |   |--- value: [1.08]
|   |   |--- T >  32.50
|   |   |   |--- TiO2 <= 0.03
|   |   |   |   |--- Al2O3 <= 0.03
|   |   |   |   |   |--- T <= 55.00
|   |   |   |   |   |   |--- T <= 47.50
|   |   |   |   |   |   |   |--- value: [1.05]
|   |   |   |   |   |   |--- T >  47.50
|   |   |   |   |   |   |   |--- value: [1.04]
|   |   |   |   |   |--- T >  55.00
|   |   |   |   |   |   |--- T <= 62.50
|   |   |   |   |   |   |   |--- value: [1.04]
|   |   |   |   |   |   |--- T >  62.50
|   |   |   |   |   |   |   |--- value: [1.03]
|   |   |   |   |--- Al2O3 >  0.03
|   |   |   |   |   |--- T <= 60.00
|   |   |   |   |   |   |--- T <= 52.50
|   |   |   |   |   |   |   |--- value: [1.07]
|   |   |   |   |   |   |--- T >  52.50
|   |   |   |   |   |   |   |--- value: [1.06]
|   |   |   |   |   |--- T >  60.00
|   |   |   |   |   |   |--- T <= 67.50
|   |   |   |   |   |   |   |--- value: [1.06]
|   |   |   |   |   |   |--- T >  67.50
|   |   |   |   |   |   |   |--- value: [1.05]
|   |   |   |--- TiO2 >  0.03
|   |   |   |   |--- T <= 50.00
|   |   |   |   |   |--- T <= 37.50
|   |   |   |   |   |   |--- value: [1.08]
|   |   |   |   |   |--- T >  37.50
|   |   |   |   |   |   |--- value: [1.08]
|   |   |   |   |--- T >  50.00
|   |   |   |   |   |--- T <= 67.50
|   |   |   |   |   |   |--- T <= 62.50
|   |   |   |   |   |   |   |--- value: [1.06]
|   |   |   |   |   |   |--- T >  62.50
|   |   |   |   |   |   |   |--- value: [1.06]
|   |   |   |   |   |--- T >  67.50
|   |   |   |   |   |   |--- value: [1.06]
|   |--- TiO2 >  0.18
|   |   |--- T <= 40.00
|   |   |   |--- T <= 30.00
|   |   |   |   |--- value: [1.22]
|   |   |   |--- T >  30.00
|   |   |   |   |--- value: [1.21]
|   |   |--- T >  40.00
|   |   |   |--- T <= 60.00
|   |   |   |   |--- T <= 52.50
|   |   |   |   |   |--- T <= 47.50
|   |   |   |   |   |   |--- value: [1.20]
|   |   |   |   |   |--- T >  47.50
|   |   |   |   |   |   |--- value: [1.19]
|   |   |   |   |--- T >  52.50
|   |   |   |   |   |--- value: [1.19]
|   |   |   |--- T >  60.00
|   |   |   |   |--- value: [1.18]
|--- Al2O3 >  0.18
|   |--- T <= 35.00
|   |   |--- T <= 22.50
|   |   |   |--- value: [1.19]
|   |   |--- T >  22.50
|   |   |   |--- T <= 27.50
|   |   |   |   |--- value: [1.18]
|   |   |   |--- T >  27.50
|   |   |   |   |--- value: [1.18]
|   |--- T >  35.00
|   |   |--- T <= 52.50
|   |   |   |--- T <= 42.50
|   |   |   |   |--- value: [1.17]
|   |   |   |--- T >  42.50
|   |   |   |   |--- T <= 47.50
|   |   |   |   |   |--- value: [1.17]
|   |   |   |   |--- T >  47.50
|   |   |   |   |   |--- value: [1.16]
|   |   |--- T >  52.50
|   |   |   |--- T <= 65.00
|   |   |   |   |--- T <= 57.50
|   |   |   |   |   |--- value: [1.16]
|   |   |   |   |--- T >  57.50
|   |   |   |   |   |--- value: [1.15]
|   |   |   |--- T >  65.00
|   |   |   |   |--- value: [1.14]

In [2]:

from src.rules import get_rules


rules = get_rules(model, features)
display(len(rules))
rules

Out[2]:

[if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (T > 32.5) and (TiO2 <= 0.025) and (Al2O3 <= 0.025) and (T > 55.0) and (T > 62.5) -> 1.033,
 if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (T > 32.5) and (TiO2 <= 0.025) and (Al2O3 <= 0.025) and (T > 55.0) and (T <= 62.5) -> 1.038,
 if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (T > 32.5) and (TiO2 <= 0.025) and (Al2O3 <= 0.025) and (T <= 55.0) and (T > 47.5) -> 1.045,
 if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (T > 32.5) and (TiO2 <= 0.025) and (Al2O3 <= 0.025) and (T <= 55.0) and (T <= 47.5) -> 1.051,
 if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (T > 32.5) and (TiO2 <= 0.025) and (Al2O3 > 0.025) and (T > 60.0) and (T > 67.5) -> 1.053,
 if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (T > 32.5) and (TiO2 > 0.025) and (T > 50.0) and (T > 67.5) -> 1.056,
 if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (T > 32.5) and (TiO2 <= 0.025) and (Al2O3 > 0.025) and (T > 60.0) and (T <= 67.5) -> 1.057,
 if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (T <= 32.5) and (TiO2 <= 0.025) and (Al2O3 <= 0.025) and (T > 22.5) -> 1.06,
 if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (T > 32.5) and (TiO2 > 0.025) and (T > 50.0) and (T <= 67.5) and (T > 62.5) -> 1.06,
 if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (T <= 32.5) and (TiO2 <= 0.025) and (Al2O3 <= 0.025) and (T <= 22.5) -> 1.062,
 if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (T > 32.5) and (TiO2 > 0.025) and (T > 50.0) and (T <= 67.5) and (T <= 62.5) -> 1.064,
 if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (T > 32.5) and (TiO2 <= 0.025) and (Al2O3 > 0.025) and (T <= 60.0) and (T > 52.5) -> 1.064,
 if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (T > 32.5) and (TiO2 <= 0.025) and (Al2O3 > 0.025) and (T <= 60.0) and (T <= 52.5) -> 1.069,
 if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (T > 32.5) and (TiO2 > 0.025) and (T <= 50.0) and (T > 37.5) -> 1.078,
 if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (T > 32.5) and (TiO2 > 0.025) and (T <= 50.0) and (T <= 37.5) -> 1.081,
 if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (T <= 32.5) and (TiO2 > 0.025) and (T > 27.5) -> 1.084,
 if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (T <= 32.5) and (TiO2 <= 0.025) and (Al2O3 > 0.025) -> 1.088,
 if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (T <= 32.5) and (TiO2 > 0.025) and (T <= 27.5) and (T > 22.5) -> 1.088,
 if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (T <= 32.5) and (TiO2 > 0.025) and (T <= 27.5) and (T <= 22.5) -> 1.091,
 if (Al2O3 > 0.175) and (T > 35.0) and (T > 52.5) and (T > 65.0) -> 1.144,
 if (Al2O3 > 0.175) and (T > 35.0) and (T > 52.5) and (T <= 65.0) and (T > 57.5) -> 1.152,
 if (Al2O3 > 0.175) and (T > 35.0) and (T > 52.5) and (T <= 65.0) and (T <= 57.5) -> 1.157,
 if (Al2O3 > 0.175) and (T > 35.0) and (T <= 52.5) and (T > 42.5) and (T > 47.5) -> 1.161,
 if (Al2O3 > 0.175) and (T > 35.0) and (T <= 52.5) and (T > 42.5) and (T <= 47.5) -> 1.166,
 if (Al2O3 > 0.175) and (T > 35.0) and (T <= 52.5) and (T <= 42.5) -> 1.17,
 if (Al2O3 <= 0.175) and (TiO2 > 0.175) and (T > 40.0) and (T > 60.0) -> 1.178,
 if (Al2O3 > 0.175) and (T <= 35.0) and (T > 22.5) and (T > 27.5) -> 1.179,
 if (Al2O3 > 0.175) and (T <= 35.0) and (T > 22.5) and (T <= 27.5) -> 1.184,
 if (Al2O3 <= 0.175) and (TiO2 > 0.175) and (T > 40.0) and (T <= 60.0) and (T > 52.5) -> 1.187,
 if (Al2O3 > 0.175) and (T <= 35.0) and (T <= 22.5) -> 1.189,
 if (Al2O3 <= 0.175) and (TiO2 > 0.175) and (T > 40.0) and (T <= 60.0) and (T <= 52.5) and (T > 47.5) -> 1.193,
 if (Al2O3 <= 0.175) and (TiO2 > 0.175) and (T > 40.0) and (T <= 60.0) and (T <= 52.5) and (T <= 47.5) -> 1.198,
 if (Al2O3 <= 0.175) and (TiO2 > 0.175) and (T <= 40.0) and (T > 30.0) -> 1.208,
 if (Al2O3 <= 0.175) and (TiO2 > 0.175) and (T <= 40.0) and (T <= 30.0) -> 1.219]

In [3]:

from src.rules import normalise_rules


rules = normalise_rules(rules)
display(len(rules))
rules

Out[3]:

[if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (T > 32.5) -> 1.033,
 if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (T > 32.5) and (T <= 62.5) -> 1.038,
 if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (T > 32.5) and (T <= 55.0) -> 1.045,
 if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (T > 32.5) and (T <= 55.0) -> 1.051,
 if (Al2O3 <= 0.175) and (Al2O3 > 0.025) and (TiO2 <= 0.175) and (T > 32.5) -> 1.053,
 if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (TiO2 > 0.025) and (T > 32.5) -> 1.056,
 if (Al2O3 <= 0.175) and (Al2O3 > 0.025) and (TiO2 <= 0.175) and (T > 32.5) and (T <= 67.5) -> 1.057,
 if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (T <= 32.5) and (T > 22.5) -> 1.06,
 if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (TiO2 > 0.025) and (T > 32.5) and (T <= 67.5) -> 1.06,
 if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (T <= 32.5) -> 1.062,
 if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (TiO2 > 0.025) and (T > 32.5) and (T <= 67.5) -> 1.064,
 if (Al2O3 <= 0.175) and (Al2O3 > 0.025) and (TiO2 <= 0.175) and (T > 32.5) and (T <= 60.0) -> 1.064,
 if (Al2O3 <= 0.175) and (Al2O3 > 0.025) and (TiO2 <= 0.175) and (T > 32.5) and (T <= 60.0) -> 1.069,
 if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (TiO2 > 0.025) and (T > 32.5) and (T <= 50.0) -> 1.078,
 if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (TiO2 > 0.025) and (T > 32.5) and (T <= 50.0) -> 1.081,
 if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (TiO2 > 0.025) and (T <= 32.5) and (T > 27.5) -> 1.084,
 if (Al2O3 <= 0.175) and (Al2O3 > 0.025) and (TiO2 <= 0.175) and (T <= 32.5) -> 1.088,
 if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (TiO2 > 0.025) and (T <= 32.5) and (T > 22.5) -> 1.088,
 if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (TiO2 > 0.025) and (T <= 32.5) -> 1.091,
 if (Al2O3 > 0.175) and (T > 35.0) -> 1.144,
 if (Al2O3 > 0.175) and (T > 35.0) and (T <= 65.0) -> 1.152,
 if (Al2O3 > 0.175) and (T > 35.0) and (T <= 65.0) -> 1.157,
 if (Al2O3 > 0.175) and (T > 35.0) and (T <= 52.5) -> 1.161,
 if (Al2O3 > 0.175) and (T > 35.0) and (T <= 52.5) -> 1.166,
 if (Al2O3 > 0.175) and (T > 35.0) and (T <= 52.5) -> 1.17,
 if (Al2O3 <= 0.175) and (TiO2 > 0.175) and (T > 40.0) -> 1.178,
 if (Al2O3 > 0.175) and (T <= 35.0) and (T > 22.5) -> 1.179,
 if (Al2O3 > 0.175) and (T <= 35.0) and (T > 22.5) -> 1.184,
 if (Al2O3 <= 0.175) and (TiO2 > 0.175) and (T > 40.0) and (T <= 60.0) -> 1.187,
 if (Al2O3 > 0.175) and (T <= 35.0) -> 1.189,
 if (Al2O3 <= 0.175) and (TiO2 > 0.175) and (T > 40.0) and (T <= 60.0) -> 1.193,
 if (Al2O3 <= 0.175) and (TiO2 > 0.175) and (T > 40.0) and (T <= 60.0) -> 1.198,
 if (Al2O3 <= 0.175) and (TiO2 > 0.175) and (T <= 40.0) and (T > 30.0) -> 1.208,
 if (Al2O3 <= 0.175) and (TiO2 > 0.175) and (T <= 40.0) -> 1.219]

In [4]:

from src.rules import delete_same_rules


rules = delete_same_rules(rules)
display(len(rules))
rules

Out[4]:

[if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (T > 32.5) -> 1.033,
 if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (T > 32.5) and (T <= 62.5) -> 1.038,
 if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (T > 32.5) and (T <= 55.0) -> 1.048,
 if (Al2O3 <= 0.175) and (Al2O3 > 0.025) and (TiO2 <= 0.175) and (T > 32.5) -> 1.053,
 if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (TiO2 > 0.025) and (T > 32.5) -> 1.056,
 if (Al2O3 <= 0.175) and (Al2O3 > 0.025) and (TiO2 <= 0.175) and (T > 32.5) and (T <= 67.5) -> 1.057,
 if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (T <= 32.5) and (T > 22.5) -> 1.06,
 if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (T <= 32.5) -> 1.062,
 if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (TiO2 > 0.025) and (T > 32.5) and (T <= 67.5) -> 1.062,
 if (Al2O3 <= 0.175) and (Al2O3 > 0.025) and (TiO2 <= 0.175) and (T > 32.5) and (T <= 60.0) -> 1.067,
 if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (TiO2 > 0.025) and (T > 32.5) and (T <= 50.0) -> 1.079,
 if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (TiO2 > 0.025) and (T <= 32.5) and (T > 27.5) -> 1.084,
 if (Al2O3 <= 0.175) and (Al2O3 > 0.025) and (TiO2 <= 0.175) and (T <= 32.5) -> 1.088,
 if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (TiO2 > 0.025) and (T <= 32.5) and (T > 22.5) -> 1.088,
 if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (TiO2 > 0.025) and (T <= 32.5) -> 1.091,
 if (Al2O3 > 0.175) and (T > 35.0) -> 1.144,
 if (Al2O3 > 0.175) and (T > 35.0) and (T <= 65.0) -> 1.155,
 if (Al2O3 > 0.175) and (T > 35.0) and (T <= 52.5) -> 1.166,
 if (Al2O3 <= 0.175) and (TiO2 > 0.175) and (T > 40.0) -> 1.178,
 if (Al2O3 > 0.175) and (T <= 35.0) and (T > 22.5) -> 1.182,
 if (Al2O3 > 0.175) and (T <= 35.0) -> 1.189,
 if (Al2O3 <= 0.175) and (TiO2 > 0.175) and (T > 40.0) and (T <= 60.0) -> 1.193,
 if (Al2O3 <= 0.175) and (TiO2 > 0.175) and (T <= 40.0) and (T > 30.0) -> 1.208,
 if (Al2O3 <= 0.175) and (TiO2 > 0.175) and (T <= 40.0) -> 1.219]

In [5]:

from src.rules import get_features, vectorize_rules

features = get_features(rules, ["T"])
print(features)

df_rules = vectorize_rules(rules, features)
df_rules.head(5)

['(Al2O3 <= 0.175)', '(Al2O3 > 0.025)', '(Al2O3 > 0.175)', '(TiO2 <= 0.175)', '(TiO2 > 0.025)', '(TiO2 > 0.175)']

Out[5]:

	(Al2O3 <= 0.175)	(Al2O3 > 0.025)	(Al2O3 > 0.175)	(TiO2 <= 0.175)	(TiO2 > 0.025)	(TiO2 > 0.175)	consequent
rule
if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (T > 32.5) -> 1.033	1	0	0	1	0	0	1.0333299999999999
if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (T > 32.5) and (T <= 62.5) -> 1.038	1	0	0	1	0	0	1.03826
if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (T > 32.5) and (T <= 55.0) -> 1.048	1	0	0	1	0	0	1.0478999999999998
if (Al2O3 <= 0.175) and (Al2O3 > 0.025) and (TiO2 <= 0.175) and (T > 32.5) -> 1.053	1	1	0	1	0	0	1.05291
if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (TiO2 > 0.025) and (T > 32.5) -> 1.056	1	0	0	1	1	0	1.05601

In [6]:

from src.cluster_helper import draw_best_clusters_plot, get_best_clusters_num

random_state = 9

X = df_rules.copy()
X = X.drop(["consequent"], axis=1)

clusters_score = get_best_clusters_num(X, random_state)
display(clusters_score)

draw_best_clusters_plot(clusters_score)

clusters_num = sorted(clusters_score.items(), key=lambda x: x[1], reverse=True)[0][0]
display(f"The best clusters count is {clusters_num}")

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.
  return fit_method(estimator, *args, **kwargs)

{2: 0.5483575964237912,
 3: 0.602943554055511,
 4: 0.8221763769597347,
 5: 1.0,
 6: 1.0}

'The best clusters count is 5'

In [7]:

from sklearn import cluster

from src.cluster_helper import print_cluster_result

kmeans = cluster.KMeans(n_clusters=clusters_num, random_state=random_state)
kmeans.fit(X)

print_cluster_result(X, clusters_num, kmeans.labels_)

Кластер 1 (5):
if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (T > 32.5) -> 1.033;
if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (T > 32.5) and (T <= 62.5) -> 1.038;
if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (T > 32.5) and (T <= 55.0) -> 1.048;
if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (T <= 32.5) and (T > 22.5) -> 1.06;
if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (T <= 32.5) -> 1.062
--------
Кластер 2 (5):
if (Al2O3 > 0.175) and (T > 35.0) -> 1.144;
if (Al2O3 > 0.175) and (T > 35.0) and (T <= 65.0) -> 1.155;
if (Al2O3 > 0.175) and (T > 35.0) and (T <= 52.5) -> 1.166;
if (Al2O3 > 0.175) and (T <= 35.0) and (T > 22.5) -> 1.182;
if (Al2O3 > 0.175) and (T <= 35.0) -> 1.189
--------
Кластер 3 (6):
if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (TiO2 > 0.025) and (T > 32.5) -> 1.056;
if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (TiO2 > 0.025) and (T > 32.5) and (T <= 67.5) -> 1.062;
if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (TiO2 > 0.025) and (T > 32.5) and (T <= 50.0) -> 1.079;
if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (TiO2 > 0.025) and (T <= 32.5) and (T > 27.5) -> 1.084;
if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (TiO2 > 0.025) and (T <= 32.5) and (T > 22.5) -> 1.088;
if (Al2O3 <= 0.175) and (TiO2 <= 0.175) and (TiO2 > 0.025) and (T <= 32.5) -> 1.091
--------
Кластер 4 (4):
if (Al2O3 <= 0.175) and (TiO2 > 0.175) and (T > 40.0) -> 1.178;
if (Al2O3 <= 0.175) and (TiO2 > 0.175) and (T > 40.0) and (T <= 60.0) -> 1.193;
if (Al2O3 <= 0.175) and (TiO2 > 0.175) and (T <= 40.0) and (T > 30.0) -> 1.208;
if (Al2O3 <= 0.175) and (TiO2 > 0.175) and (T <= 40.0) -> 1.219
--------
Кластер 5 (4):
if (Al2O3 <= 0.175) and (Al2O3 > 0.025) and (TiO2 <= 0.175) and (T > 32.5) -> 1.053;
if (Al2O3 <= 0.175) and (Al2O3 > 0.025) and (TiO2 <= 0.175) and (T > 32.5) and (T <= 67.5) -> 1.057;
if (Al2O3 <= 0.175) and (Al2O3 > 0.025) and (TiO2 <= 0.175) and (T > 32.5) and (T <= 60.0) -> 1.067;
if (Al2O3 <= 0.175) and (Al2O3 > 0.025) and (TiO2 <= 0.175) and (T <= 32.5) -> 1.088
--------

In [8]:

density_train = pd.read_csv("data/density_train.csv", sep=";", decimal=",")
density_test = pd.read_csv("data/density_test.csv", sep=";", decimal=",")

display(density_train.head(3))
display(density_test.head(3))

	T	Density
0	20	1.06250
1	25	1.05979
2	35	1.05404

	T	Al2O3	Density
0	30	0.00	1.05696
1	55	0.00	1.04158
2	25	0.05	1.08438

In [9]:

from src.rules import simplify_and_group_rules

clustered_rules = simplify_and_group_rules(density_train, rules, clusters_num, kmeans.labels_)
clustered_rules

Out[9]:

[[if (Al2O3 = 0.0) and (TiO2 = 0.0) and (T = 70) -> 1.033,
  if (Al2O3 = 0.0) and (TiO2 = 0.0) and (T = 47.5) -> 1.038,
  if (Al2O3 = 0.0) and (TiO2 = 0.0) and (T = 43.75) -> 1.048,
  if (Al2O3 = 0.0) and (TiO2 = 0.0) and (T = 27.5) -> 1.06,
  if (Al2O3 = 0.0) and (TiO2 = 0.0) and (T = 20) -> 1.062],
 [if (Al2O3 = 0.3) and (T = 70) -> 1.144,
  if (Al2O3 = 0.3) and (T = 50.0) -> 1.155,
  if (Al2O3 = 0.3) and (T = 43.75) -> 1.166,
  if (Al2O3 = 0.3) and (T = 28.75) -> 1.182,
  if (Al2O3 = 0.3) and (T = 20) -> 1.189],
 [if (Al2O3 = 0.0) and (TiO2 = 0.1) and (T = 70) -> 1.056,
  if (Al2O3 = 0.0) and (TiO2 = 0.1) and (T = 50.0) -> 1.062,
  if (Al2O3 = 0.0) and (TiO2 = 0.1) and (T = 41.25) -> 1.079,
  if (Al2O3 = 0.0) and (TiO2 = 0.1) and (T = 30.0) -> 1.084,
  if (Al2O3 = 0.0) and (TiO2 = 0.1) and (T = 27.5) -> 1.088,
  if (Al2O3 = 0.0) and (TiO2 = 0.1) and (T = 20) -> 1.091],
 [if (Al2O3 = 0.0) and (TiO2 = 0.3) and (T = 70) -> 1.178,
  if (Al2O3 = 0.0) and (TiO2 = 0.3) and (T = 50.0) -> 1.193,
  if (Al2O3 = 0.0) and (TiO2 = 0.3) and (T = 35.0) -> 1.208,
  if (Al2O3 = 0.0) and (TiO2 = 0.3) and (T = 20) -> 1.219],
 [if (Al2O3 = 0.1) and (TiO2 = 0.0) and (T = 70) -> 1.053,
  if (Al2O3 = 0.1) and (TiO2 = 0.0) and (T = 50.0) -> 1.057,
  if (Al2O3 = 0.1) and (TiO2 = 0.0) and (T = 46.25) -> 1.067,
  if (Al2O3 = 0.1) and (TiO2 = 0.0) and (T = 20) -> 1.088]]

In [10]:

import numpy as np
from skfuzzy import control as ctrl
import skfuzzy as fuzz

temp = ctrl.Antecedent(density_train["T"].sort_values().unique(), "temp")
al = ctrl.Antecedent(np.arange(0, 0.3, 0.005), "al")
ti = ctrl.Antecedent(np.arange(0, 0.3, 0.005), "ti")
density = ctrl.Consequent(np.arange(1.03, 1.22, 0.00001), "density")

temp.automf(3, variable_type="quant")
temp.view()
al.automf(3, variable_type="quant")
al.view()
ti.automf(3, variable_type="quant")
ti.view()
density.automf(5, variable_type="quant")
density.view()

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
  fig.show()

In [11]:

from src.rules import  get_fuzzy_rules

fuzzy_variables = {"Al2O3": al, "TiO2": ti, "T": temp, "consequent": density}
fuzzy_rules = get_fuzzy_rules(clustered_rules, fuzzy_variables)

fuzzy_cntrl = ctrl.ControlSystem(fuzzy_rules)

sim = ctrl.ControlSystemSimulation(fuzzy_cntrl, lenient=False)

display(len(fuzzy_rules))
fuzzy_rules

Out[11]:

[IF (al[low] AND ti[low]) AND temp[high] THEN density[lower]
 	AND aggregation function : fmin
 	OR aggregation function  : fmax,
 IF (al[low] AND ti[low]) AND temp[average] THEN density[lower]
 	AND aggregation function : fmin
 	OR aggregation function  : fmax,
 IF (al[low] AND ti[low]) AND temp[low] THEN density[low]
 	AND aggregation function : fmin
 	OR aggregation function  : fmax,
 IF al[high] AND temp[high] THEN density[average]
 	AND aggregation function : fmin
 	OR aggregation function  : fmax,
 IF al[high] AND temp[average] THEN density[high]
 	AND aggregation function : fmin
 	OR aggregation function  : fmax,
 IF al[high] AND temp[low] THEN density[high]
 	AND aggregation function : fmin
 	OR aggregation function  : fmax,
 IF (al[low] AND ti[average]) AND temp[high] THEN density[low]
 	AND aggregation function : fmin
 	OR aggregation function  : fmax,
 IF (al[low] AND ti[average]) AND temp[average] THEN density[low]
 	AND aggregation function : fmin
 	OR aggregation function  : fmax,
 IF (al[low] AND ti[average]) AND temp[low] THEN density[low]
 	AND aggregation function : fmin
 	OR aggregation function  : fmax,
 IF (al[low] AND ti[high]) AND temp[high] THEN density[high]
 	AND aggregation function : fmin
 	OR aggregation function  : fmax,
 IF (al[low] AND ti[high]) AND temp[average] THEN density[higher]
 	AND aggregation function : fmin
 	OR aggregation function  : fmax,
 IF (al[low] AND ti[high]) AND temp[low] THEN density[higher]
 	AND aggregation function : fmin
 	OR aggregation function  : fmax,
 IF (al[average] AND ti[low]) AND temp[high] THEN density[lower]
 	AND aggregation function : fmin
 	OR aggregation function  : fmax,
 IF (al[average] AND ti[low]) AND temp[average] THEN density[low]
 	AND aggregation function : fmin
 	OR aggregation function  : fmax,
 IF (al[average] AND ti[low]) AND temp[low] THEN density[low]
 	AND aggregation function : fmin
 	OR aggregation function  : fmax]

In [12]:

sim.input["temp"] = 20
sim.input["al"] = 0.0
sim.input["ti"] = 0.0
sim.compute()
sim.print_state()
display(sim.output["density"])

=============
 Antecedents 
=============
Antecedent: al                      = 0.0
  - low                             : 1.0
  - average                         : 0.0
  - high                            : 0.0
Antecedent: ti                      = 0.0
  - low                             : 1.0
  - average                         : 0.0
  - high                            : 0.0
Antecedent: temp                    = 20
  - low                             : 1.0
  - average                         : 0.0
  - high                            : 0.0

=======
 Rules 
=======
RULE #0:
  IF (al[low] AND ti[low]) AND temp[high] THEN density[lower]
	AND aggregation function : fmin
	OR aggregation function  : fmax

  Aggregation (IF-clause):
  - al[low]                                                : 1.0
  - ti[low]                                                : 1.0
  - temp[high]                                             : 0.0
                      (al[low] AND ti[low]) AND temp[high] = 0.0
  Activation (THEN-clause):
                                            density[lower] : 0.0

RULE #1:
  IF (al[low] AND ti[low]) AND temp[average] THEN density[lower]
	AND aggregation function : fmin
	OR aggregation function  : fmax

  Aggregation (IF-clause):
  - al[low]                                                : 1.0
  - ti[low]                                                : 1.0
  - temp[average]                                          : 0.0
                   (al[low] AND ti[low]) AND temp[average] = 0.0
  Activation (THEN-clause):
                                            density[lower] : 0.0

RULE #2:
  IF (al[low] AND ti[low]) AND temp[low] THEN density[low]
	AND aggregation function : fmin
	OR aggregation function  : fmax

  Aggregation (IF-clause):
  - al[low]                                                : 1.0
  - ti[low]                                                : 1.0
  - temp[low]                                              : 1.0
                       (al[low] AND ti[low]) AND temp[low] = 1.0
  Activation (THEN-clause):
                                              density[low] : 1.0

RULE #3:
  IF al[high] AND temp[high] THEN density[average]
	AND aggregation function : fmin
	OR aggregation function  : fmax

  Aggregation (IF-clause):
  - al[high]                                               : 0.0
  - temp[high]                                             : 0.0
                                   al[high] AND temp[high] = 0.0
  Activation (THEN-clause):
                                          density[average] : 0.0

RULE #4:
  IF al[high] AND temp[average] THEN density[high]
	AND aggregation function : fmin
	OR aggregation function  : fmax

  Aggregation (IF-clause):
  - al[high]                                               : 0.0
  - temp[average]                                          : 0.0
                                al[high] AND temp[average] = 0.0
  Activation (THEN-clause):
                                             density[high] : 0.0

RULE #5:
  IF al[high] AND temp[low] THEN density[high]
	AND aggregation function : fmin
	OR aggregation function  : fmax

  Aggregation (IF-clause):
  - al[high]                                               : 0.0
  - temp[low]                                              : 1.0
                                    al[high] AND temp[low] = 0.0
  Activation (THEN-clause):
                                             density[high] : 0.0

RULE #6:
  IF (al[low] AND ti[average]) AND temp[high] THEN density[low]
	AND aggregation function : fmin
	OR aggregation function  : fmax

  Aggregation (IF-clause):
  - al[low]                                                : 1.0
  - ti[average]                                            : 0.0
  - temp[high]                                             : 0.0
                  (al[low] AND ti[average]) AND temp[high] = 0.0
  Activation (THEN-clause):
                                              density[low] : 0.0

RULE #7:
  IF (al[low] AND ti[average]) AND temp[average] THEN density[low]
	AND aggregation function : fmin
	OR aggregation function  : fmax

  Aggregation (IF-clause):
  - al[low]                                                : 1.0
  - ti[average]                                            : 0.0
  - temp[average]                                          : 0.0
               (al[low] AND ti[average]) AND temp[average] = 0.0
  Activation (THEN-clause):
                                              density[low] : 0.0

RULE #8:
  IF (al[low] AND ti[average]) AND temp[low] THEN density[low]
	AND aggregation function : fmin
	OR aggregation function  : fmax

  Aggregation (IF-clause):
  - al[low]                                                : 1.0
  - ti[average]                                            : 0.0
  - temp[low]                                              : 1.0
                   (al[low] AND ti[average]) AND temp[low] = 0.0
  Activation (THEN-clause):
                                              density[low] : 0.0

RULE #9:
  IF (al[low] AND ti[high]) AND temp[high] THEN density[high]
	AND aggregation function : fmin
	OR aggregation function  : fmax

  Aggregation (IF-clause):
  - al[low]                                                : 1.0
  - ti[high]                                               : 0.0
  - temp[high]                                             : 0.0
                     (al[low] AND ti[high]) AND temp[high] = 0.0
  Activation (THEN-clause):
                                             density[high] : 0.0

RULE #10:
  IF (al[low] AND ti[high]) AND temp[average] THEN density[higher]
	AND aggregation function : fmin
	OR aggregation function  : fmax

  Aggregation (IF-clause):
  - al[low]                                                : 1.0
  - ti[high]                                               : 0.0
  - temp[average]                                          : 0.0
                  (al[low] AND ti[high]) AND temp[average] = 0.0
  Activation (THEN-clause):
                                           density[higher] : 0.0

RULE #11:
  IF (al[low] AND ti[high]) AND temp[low] THEN density[higher]
	AND aggregation function : fmin
	OR aggregation function  : fmax

  Aggregation (IF-clause):
  - al[low]                                                : 1.0
  - ti[high]                                               : 0.0
  - temp[low]                                              : 1.0
                      (al[low] AND ti[high]) AND temp[low] = 0.0
  Activation (THEN-clause):
                                           density[higher] : 0.0

RULE #12:
  IF (al[average] AND ti[low]) AND temp[high] THEN density[lower]
	AND aggregation function : fmin
	OR aggregation function  : fmax

  Aggregation (IF-clause):
  - al[average]                                            : 0.0
  - ti[low]                                                : 1.0
  - temp[high]                                             : 0.0
                  (al[average] AND ti[low]) AND temp[high] = 0.0
  Activation (THEN-clause):
                                            density[lower] : 0.0

RULE #13:
  IF (al[average] AND ti[low]) AND temp[average] THEN density[low]
	AND aggregation function : fmin
	OR aggregation function  : fmax

  Aggregation (IF-clause):
  - al[average]                                            : 0.0
  - ti[low]                                                : 1.0
  - temp[average]                                          : 0.0
               (al[average] AND ti[low]) AND temp[average] = 0.0
  Activation (THEN-clause):
                                              density[low] : 0.0

RULE #14:
  IF (al[average] AND ti[low]) AND temp[low] THEN density[low]
	AND aggregation function : fmin
	OR aggregation function  : fmax

  Aggregation (IF-clause):
  - al[average]                                            : 0.0
  - ti[low]                                                : 1.0
  - temp[low]                                              : 1.0
                   (al[average] AND ti[low]) AND temp[low] = 0.0
  Activation (THEN-clause):
                                              density[low] : 0.0


==============================
 Intermediaries and Conquests 
==============================
Consequent: density                  = 1.0774975002635008
  lower:
    Accumulate using accumulation_max : 0.0
  low:
    Accumulate using accumulation_max : 1.0
  average:
    Accumulate using accumulation_max : 0.0
  high:
    Accumulate using accumulation_max : 0.0
  higher:
    Accumulate using accumulation_max : 0.0

np.float64(1.0774975002635008)

In [13]:

def fuzzy_pred(row):
    sim.input["temp"] = row["T"]
    sim.input["al"] = row["Al2O3"]
    sim.input["ti"] = row["TiO2"]
    sim.compute()
    return sim.output["density"]

result_train = density_train.copy()
result_train["DensityPred"] = result_train.apply(fuzzy_pred, axis=1)
result_train.head(15)

Out[13]:

	T	Al2O3	Density	DensityPred
0	20	0.00	1.06250	1.077498
1	25	0.00	1.05979	1.076593
2	35	0.00	1.05404	1.069156
3	40	0.00	1.05103	1.061106
4	45	0.00	1.04794	1.045833
5	50	0.00	1.04477	1.046360
6	60	0.00	1.03826	1.047642
7	65	0.00	1.03484	1.046360
8	70	0.00	1.03182	1.045833
9	20	0.05	1.08755	1.077498
10	45	0.05	1.07105	1.067145
11	50	0.05	1.06760	1.067145
12	55	0.05	1.06409	1.067988
13	65	0.05	1.05691	1.062538
14	70	0.05	1.05291	1.047191

In [14]:

result_test = density_test.copy()
result_test["DensityPred"] = result_test.apply(fuzzy_pred, axis=1)
result_test

Out[14]:

	T	Al2O3	TiO2	Density	DensityPred
0	30	0.00	0.00	1.05696	1.073918
1	55	0.00	0.00	1.04158	1.047642
2	25	0.05	0.00	1.08438	1.076518
3	30	0.05	0.00	1.08112	1.073918
4	35	0.05	0.00	1.07781	1.069156
5	40	0.05	0.00	1.07446	1.067145
6	60	0.05	0.00	1.06053	1.067988
7	35	0.30	0.00	1.17459	1.172492
8	65	0.30	0.00	1.14812	1.136460
9	45	0.00	0.05	1.07424	1.067145
10	50	0.00	0.05	1.07075	1.067145
11	55	0.00	0.05	1.06721	1.067988
12	20	0.00	0.30	1.22417	1.204157
13	30	0.00	0.30	1.21310	1.202348
14	40	0.00	0.30	1.20265	1.203630
15	60	0.00	0.30	1.18265	1.176072
16	70	0.00	0.30	1.17261	1.172492

In [15]:

import math
from sklearn import metrics


rmetrics = {}
rmetrics["RMSE_train"] = math.sqrt(
    metrics.mean_squared_error(result_train["Density"], result_train["DensityPred"])
)
rmetrics["RMSE_test"] = math.sqrt(
    metrics.mean_squared_error(result_test["Density"], result_test["DensityPred"])
)
rmetrics["RMAE_test"] = math.sqrt(
    metrics.mean_absolute_error(result_test["Density"], result_test["DensityPred"])
)
rmetrics["R2_test"] = metrics.r2_score(
    result_test["Density"], result_test["DensityPred"]
)

rmetrics

Out[15]:

{'RMSE_train': 0.009765373953597112,
 'RMSE_test': 0.009031443610368107,
 'RMAE_test': 0.08581225574298121,
 'R2_test': 0.978451748357252}

287 KiB Raw Blame History

287 KiB

Raw Blame History