January 9, 2021
Decision Trees are notoriously famous for overfitting. Bagging exploit this weakness of Decision Trees to its advantage. Each tree is fed with a different subset of data and the make predictions which are significantly different from one another. By aggregating their outputs bagging averages out the polar tendencies and thus significantly improves generalization.
by : Monis Khan
Quick Summary:
Decision Trees are notoriously famous for overfitting. Bagging exploit this weakness of Decision Trees to its advantage. Each tree is fed with a different subset of data and the make predictions which are significantly different from one another. By aggregating their outputs bagging averages out the polar tendencies and thus significantly improves generalization.