imb_pipe2.py

model = make_pipeline_imb(TfidfVectorizer(), RandomUnderSampler(), MultinomialNB())

model.fit(X_train, y_train)
y_pred = model.predict(X_test)

print(classification_report(y_test,y_pred))

#            precision    recall  f1-score   support
#
#          0       0.73      0.87      0.79       319
#           1       0.97      0.86      0.91       389
#           2       0.95      0.90      0.93       394
#           3       0.76      0.76      0.76       251

#    accuracy                           0.86      1353
#   macro avg       0.85      0.85      0.85      1353
#weighted avg       0.87      0.86      0.86      1353