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
SMOTENC should be inserted before the classifier
('clf', reg) but I don't know how to define "
SMOTENC. Besides, could you please let me know where to use imblearn.pipeline?
Thanks in advance.