What are common mistakes when using SMOTE?

What are common mistakes when using SMOTE?

Some common mistakes include not tuning the parameters, applying SMOTE to the entire dataset, and ignoring the impact on model performance.

Can you explain why applying SMOTE to the entire dataset is a mistake?

Applying SMOTE to the entire dataset can lead to data leakage, as it creates synthetic samples based on the test data, which can skew results.

What parameters should I tune when using SMOTE?

You should consider tuning the 'sampling_strategy', 'k_neighbors', and 'random_state' parameters to optimize performance.

How can I evaluate the impact of SMOTE on my model?

You can evaluate the impact by comparing metrics like accuracy, precision, recall, and F1-score before and after applying SMOTE.

Are there alternatives to SMOTE I should consider?

Yes, alternatives include ADASYN, Borderline-SMOTE, and using ensemble methods like Random Forest with class weights.