What is the main advantage of gradient boosting over bagging?

Handles categorical data better

Focuses on correcting previous errors

Requires less computation

Less prone to overfitting

Gradient boosting sequentially corrects errors of previous models, often outperforming bagging in accuracy.

Strengthen Your Practice with our comprehensive question bank.

Get Expert Advice for Free: Register for Your Free Consultation Now!

Full Name

Phone Number

Select Language

Select Course

Please leave this field empty.