What is the impact of class weight in machine learning?

What is the impact of class weight in machine learning?

Class weight helps to address class imbalance by assigning different weights to classes during training.

How does it affect model performance?

Adjusting class weights can improve the model's ability to predict minority classes, leading to better overall performance.

Can you give an example of when to use class weights?

Sure! In a dataset where 90% of the samples belong to one class, using class weights can help the model learn from the minority class.

Are there any downsides to using class weights?

Yes, if not set properly, class weights can lead to overfitting on the minority class or underfitting on the majority class.