Ensemble Methods (51222899322).jpg
Ensemble Methods help to create multiple models and then combine them to produce improved results: 1. BAGGing (Bootstrap AGGregating) reduces the high variance of the model. 2. Boosting makes out a stronger learner model from weak learner models by averaging their weights. 3. Stacking combines multiple classifications or regression techniques using a meta-classifier or meta-model. Part of Geeklendar 2021 <a href="https://exeypanteleev.com/geeklendar" rel="noreferrer nofollow">exeypanteleev.com/geeklendar</a>
Artist: Exey Panteleev from Moscow, Russia. License: CC BY 2.0. Source
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