Hyperparameter Tuning and Sampling Strategy

Finding the best sampling strategy using pipelines and hyperparameter tuning

One of the go-to steps in handling imbalanced machine learning problems is to resample the data. We can either undersample the majority class and/or oversample the minority class. However, there is a question that needs to be addressed: to what number should we reduce the majority class, and/or increase the minority class? An easy but time-consuming method is to alter the resampling values of the majority and minority classes one …

hyperparameter hyperparameter-tuning machine learning oversampling pipeline sampling strategy undersampling