ट्री-आधारित फीचर चयन

Python में Dimensionality Reduction

Jeroen Boeye

Head of Machine Learning, Faktion

Random forest classifier

रैंडम फ़ॉरेस्ट स्कीमा

Random forest classifier

from sklearn.ensemble import RandomForestClassifier
from sklearn.metrics import accuracy_score

rf = RandomForestClassifier()

rf.fit(X_train, y_train)

print(accuracy_score(y_test, rf.predict(X_test)))

0.99

Random forest classifier

टिप्पणी सहित रैंडम फ़ॉरेस्ट स्कीमा

फीचर इम्पोर्टेंस वैल्यूज़

rf = RandomForestClassifier()

rf.fit(X_train, y_train)

print(rf.feature_importances_)

array([0.  , 0.  , 0.  , 0.  , 0.  , 0.  , 0.  , 0.04, 0.  , 0.01, 0.01,
       0.  , 0.  , 0.  , 0.  , 0.01, 0.01, 0.  , 0.  , 0.  , 0.  , 0.05,
       ...
       0.  , 0.14, 0.  , 0.  , 0.  , 0.06, 0.  , 0.  , 0.  , 0.  , 0.  ,
       0.  , 0.07, 0.  , 0.  , 0.01, 0.  ])

print(sum(rf.feature_importances_))

1.0

फीचर चयनक के रूप में फीचर इम्पोर्टेंस

mask = rf.feature_importances_ > 0.1

print(mask)

array([False, False, ..., True, False])

X_reduced = X.loc[:, mask]

print(X_reduced.columns)

Index(['chestheight', 'neckcircumference', 'neckcircumferencebase',
       'shouldercircumference'], dtype='object')

रैंडम फ़ॉरेस्ट्स के साथ RFE

from sklearn.feature_selection import RFE

rfe = RFE(estimator=RandomForestClassifier(), 
          n_features_to_select=6, verbose=1)

rfe.fit(X_train,y_train)

Fitting estimator with 94 features.
Fitting estimator with 93 features
...
Fitting estimator with 8 features.
Fitting estimator with 7 features.

print(accuracy_score(y_test, rfe.predict(X_test))

0.99

रैंडम फ़ॉरेस्ट्स के साथ RFE

from sklearn.feature_selection import RFE

rfe = RFE(estimator=RandomForestClassifier(), 
          n_features_to_select=6, step=10, verbose=1)

rfe.fit(X_train,y_train)

Fitting estimator with 94 features.
Fitting estimator with 84 features.
...
Fitting estimator with 24 features.
Fitting estimator with 14 features.

print(X.columns[rfe.support_])

Index(['biacromialbreadth', 'handbreadth', 'handcircumference', 
       'neckcircumference', 'neckcircumferencebase', 'shouldercircumference'], dtype='object')

अभ्यास करते हैं!

Python में Dimensionality Reduction