title: Using Smote with Gridsearchcv in Scikit-learn
body: <p>I'm dealing with an imbalanced dataset and want to do a grid search to tune my model's parameters using scikit's gridsearchcv. To oversample the data, I want to use SMOTE, and I know I can include that as a stage of a pipeline and pass it to gridsearchcv.
  My concern is that I think smote will be applied to both train and validation folds, which is not what you are supposed to do. The validation set should not be oversampled.
  Am I right that the whole pipeline will be applied to both dataset splits? And if yes, how can I turn around this?
  Thanks a lot in advance</p>