CODEWITHSUNDEEP
pythonscikit-learnsklearn-pandas
Grygger
Grygger

Reputation: 93

RandomForestClassifier - Odd error with trying to identify feature importance in sklearn?

I'm trying to retrieve the importance of features within a RandomForestClassifier model, retrieving the coef for each feature in the model,

I'm running the following code here,

random_forest =  SelectFromModel(RandomForestClassifier(n_estimators = 200, random_state = 123))
random_forest.fit(X_train, y_train)
print(random_forest.estimator.feature_importances_)

but am receiving the following error

NotFittedError: This RandomForestClassifier instance is not fitted yet. Call 'fit' with appropriate arguments before using this method.

What exactly am I doing wrong? You can see I fit the model right before looking to identify the importance of features, but it doesn't seem to work as it should,

Similarily, I have the code below with a LogisticRegression model and it works fine,

log_reg = SelectFromModel(LogisticRegression(class_weight = "balanced", random_state = 123))
log_reg.fit(X_train, y_train)
print(log_reg.estimator_.coef_)

Upvotes: 0

Views: 36

Answers (1)

afsharov
afsharov

Reputation: 5164

You have to call the attribute estimator_ to access the fitted estimator (see the docs). Observe that you forgot the trailing _. So it should be:

print(random_forest.estimator_.feature_importances_)

Interestingly, you did it correctly for your example with the LogisticRegression model.

Upvotes: 1

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