Bagging

An ensembling technique. When bagging, each model is trained on random subset of the rows, and a random subset of the columns, with replacement.

“with replacement” means that if a model, for example, randomly chooses row number 5, another model can also randomly choose row number 5.

Through this technique, each model ends up training on roughly 63% of the entire dataset.

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