Sklearn: ROC for multiclass classification
问题 I'm doing different text classification experiments. Now I need to calculate the AUC-ROC for each task. For the binary classifications, I already made it work with this code: scaler = StandardScaler(with_mean=False) enc = LabelEncoder() y = enc.fit_transform(labels) feat_sel = SelectKBest(mutual_info_classif, k=200) clf = linear_model.LogisticRegression() pipe = Pipeline([('vectorizer', DictVectorizer()), ('scaler', StandardScaler(with_mean=False)), ('mutual_info', feat_sel), ('logistregress'