Thanks. The code is provided here: https://github.com/scikit-learn-contrib/imbalanced-learn/issues/537
Best regards, On Thu, Jan 24, 2019 at 7:15 PM Guillaume Lemaître <g.lemaitr...@gmail.com> wrote: > You should open a ticket on imbalanced-learn GitHub issue. This is easier > to post a reproducible example and for us to test it. > From the error message, I can understand that you have 161 features and > require a feature above the index 160. > > > > On Thu, 24 Jan 2019 at 16:19, S Hamidizade <hamidizad...@gmail.com> wrote: > >> Thanks. Unfortunately, now the error is: >> ValueError: Some of the categorical indices are out of range. Indices >> should be between 0 and 160. >> Best regards, >> >> On Sun, Jan 20, 2019 at 8:31 PM S Hamidizade <hamidizad...@gmail.com> >> wrote: >> >>> 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, >>> >> _______________________________________________ >> scikit-learn mailing list >> scikit-learn@python.org >> https://mail.python.org/mailman/listinfo/scikit-learn >> > > > -- > Guillaume Lemaitre > INRIA Saclay - Parietal team > Center for Data Science Paris-Saclay > https://glemaitre.github.io/ > _______________________________________________ > scikit-learn mailing list > scikit-learn@python.org > https://mail.python.org/mailman/listinfo/scikit-learn >
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