How can I handle class imbalance in my machine learning model?

How can I handle class imbalance in my machine learning model?

You can handle class imbalance using techniques like resampling, using different algorithms, or adjusting class weights.

What is resampling, and how does it work?

Resampling involves either oversampling the minority class or undersampling the majority class to balance the dataset.

Are there specific algorithms that work better with imbalanced data?

Yes, algorithms like Random Forest and Gradient Boosting can be more robust to class imbalance.

How do I adjust class weights in my model?

You can adjust class weights by using the class_weight parameter in models like Logistic Regression or SVM.