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BAGGING vs. BOOSTING vs STACKING in Ensemble Learning | Machine Learning

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Bagging, Boosting, and Stacking are three key ensemble methods in machine learning, each designed to enhance model accuracy in different ways. In this video, we’ll break down how each technique works, their differences, and when to use them to get the best results from your models.

00:00 – Introduction
00:16 – Bagging
02:49 – Boosting
04:34 – Stacking

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