What is Ensemble learning?

Ensemble learning is a common meta-approach to machine learning that aims to improve prediction performance by combining predictions from multiple models.

His three main classes of ensemble learning methods are bagging, stacking, and boosting. It's important to understand each method in detail and consider them in your predictive modeling projects.

NOTE:: Machine learning refers to the process of training computer programs to build statistical models based on data. Machine learning interview questions help clarify every interview based on machine learning.