What is class weight importance in machine learning?

What is class weight importance in machine learning?

Class weight importance refers to the technique of assigning different weights to classes in a dataset to address class imbalance.

Why is it important to use class weights?

Using class weights helps improve the model's performance on underrepresented classes, ensuring better predictions.

How do I implement class weights in my model?

You can implement class weights in libraries like Scikit-learn by using the 'class_weight' parameter in your model.

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

Sure! If you have a dataset with 90% of one class and only 10% of another, using class weights can help balance the learning.