How do I tune SMOTE parameters for better model performance?

How do I tune SMOTE parameters for better model performance?

Tuning SMOTE parameters involves adjusting the sampling strategy, k-neighbors, and random state. What specific issues are you facing?

I'm not sure how to choose the right sampling strategy.

The sampling strategy can be a float or a dictionary. A float represents the desired ratio of minority to majority samples. A common starting point is 0.5.

What about the k-neighbors parameter?

The k-neighbors parameter determines how many nearest neighbors are used to generate synthetic samples. A typical value is between 5 and 10, but you can experiment with it.

How can I evaluate the impact of these changes?

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