Bagging
Learn how bagging is the first technique used by the random forest algorithm to produce valuable ensembles.
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Randomizing observations
To build a valuable machine learning ensemble, the models within the ensemble should produce predictions with low correlation. In other words, the ensemble models should be different from each other. The random forest algorithm takes advantage of the high variance of the CART algorithm to manufacture diversity across the ensemble models.
The random forest algorithm uses bagging (i.e., bootstrap aggregation) to randomize the observations ...