ML Interview Question: Bagging and Boosting?

Anvi_Singh

Explain bagging and boosting.

Niranjan sahoo

vikram

Bagging and Boosting are two types of Ensemble Learning.
Bagging :- Dataset is divided into different dataset randomly and train to different classifiers model , after that voting of all model is done independently then after different voting counting technique decision is made

Boosting :- whole data is passed (trained) to single classifier , then before passing to other classifer model error correction (adaptive learning) is done