The boosting process in the creating ensemble models step in the AutoML process serves the purpose of
A) extracting new insights from data.
B) boosting noise and bias.
C) reducing error in the model.
D) calculating the sum of predictions from multiple models.

Question

Quizplus · Accepted Answer

Boosting is a technique used in ensemble models to reduce error by sequentially correcting the mistakes of weak learners, thereby improving the overall model's accuracy.

The Boosting Process in the Creating Ensemble Models Step in the AutoML