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Recall for overview of ensemble algorithms which was already discussed on Day80, I learned more detail about bagging (Bootstrap aggregating), boosting, and stacking (Staked Generalization)
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I learned in this video about Bagging, Boosting, and stacking.
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I learned in this Bagging, Boosting, and Stacking.
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AOA, I learned in this lecture about the ML algorithm of Ensemble Methods (combine several base model in order to produce one optimal model) and its types Which are1- Bagging ( bootstrap aggregation) ( parallel tree growing with sub-samples )
2- Boosting( sequential tree growth with weighted samples ) ( makes a weak learner strong )
3- Stacking ( Stacked Generalization )
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