Dear Scikit-learners Hi. I would greatly appreciate if you could let me know how to use SMOTENC. I wrote:
num_indices1 = list(X.iloc[:,np.r_[0:94,95,97,100:123]].columns.values) cat_indices1 = list(X.iloc[:,np.r_[94,96,98,99,123:160]].columns.values) print(len(num_indices1)) print(len(cat_indices1)) pipeline=Pipeline(steps= [ # Categorical features ('feature_processing', FeatureUnion(transformer_list = [ ('categorical', MultiColumn(cat_indices1)), #numeric ('numeric', Pipeline(steps = [ ('select', MultiColumn(num_indices1)), ('scale', StandardScaler()) ])) ])), ('clf', rg) ] ) Therefore, as it is indicated I have 5 categorical features. Really, indices 123 to 160 are related to one categorical feature with 37 possible values which is converted into 37 columns using get_dummies. Sorry, I think SMOTENC should be inserted before the classifier ('clf', reg) but I don't know how to define "categorical_features" in SMOTENC. Besides, could you please let me know where to use imblearn.pipeline? Thanks in advance. Best regards,
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