Scikit-learn model representation

Question

Suppose, i have some models created and fitted in scikit-learn.

model_rc = RidgeClassifier(class_weight='auto')
model_rc.fit(x_train, y_train)

model_dt = DecisionTreeClassifier()
model_dt.fit(x_train, y_train)

...

How can i get linear coefficients for RidgeClassifier or tree for DecisionTree.

In other words, I'm looking for R summary analogue in scikit-learn.

Thanks in advance!

Answer 1

I am not sure if there is a summary analog in sklearn, but you can get coefficients of ridge via model_rc.coef_ and model_rc.intercept_, and you can seemingly get the tree via model_dt.tree_.

I have never tried to do anything with trees, so I don't know what you can do with that tree object. There is also a possibility to get its visual representation, check out this post.