Machine Learning & Training

What Is Bagging?

Bagging, short for bootstrap aggregating, is an ensemble method that trains multiple models on different random samples of the data. The models' predictions are then combined, typically by averaging or voting. This reduces variance and helps prevent overfitting, and it forms the basis of the random forest algorithm.