What is class imbalance in machine learning and why is it important?

What is class imbalance in machine learning and why is it important?

Class imbalance occurs when the number of instances in different classes is not equal, which can lead to biased models.

How does class imbalance affect model performance?

It can cause the model to be biased towards the majority class, leading to poor predictions for the minority class.

What techniques can be used to handle class imbalance?

Common techniques include resampling methods, using different algorithms, and applying cost-sensitive learning.

Can you give an example of a real-world application affected by class imbalance?

Sure! Fraud detection is a classic example where fraudulent transactions are much rarer than legitimate ones.