Problem with sklearn.ensemble.LogisticRegression()

[malmashhadani]

When I run the
feat_selector = BorutaPy(LRmodel, n_estimators='auto', verbose=2)
then I run:
feat_selector.fit(training_data.drop(columns=['LeadID','Enrolled_flag','CreateDate','LeadPrice']), training_data.Enrolled_flag)

I get the error

depth = self.estimator.get_params()['max_depth']

KeyError: 'max_depth'

[JosAndr]

Logistic regression don't have "max_depth" as parameter, im not sure but i htink thaht boruta is not intended for use LR as estimator, the original algorithm is based on random forest