What is the impact of class imbalance in machine learning?

What is the impact of class imbalance in machine learning?

Class imbalance occurs when the classes in a dataset are not represented equally, which can lead to biased models.

How does it 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 address 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 common example, where fraudulent transactions are much rarer than legitimate ones.