What are some alternative techniques for handling class imbalance in datasets?

What are some alternative techniques for handling class imbalance in datasets?

There are several techniques to address class imbalance, such as resampling methods, synthetic data generation, and cost-sensitive learning.

Can you explain resampling methods?

Sure! Resampling methods include oversampling the minority class or undersampling the majority class to create a balanced dataset.

What is synthetic data generation?

Synthetic data generation involves creating new samples for the minority class using techniques like SMOTE (Synthetic Minority Over-sampling Technique).

How does cost-sensitive learning work?

Cost-sensitive learning assigns different costs to misclassifications, making the model more sensitive to the minority class.