Two’s Company, Three’s an Ensemble

Ensemble techniques — wherein a predictive model is composed of multiple (possibly) weaker models — are prevalent nowadays within the field of machine learning (ML) and deep learning (DL). Well-known methods such as bagging, boosting, and stacking are ML mainstays, widely (and fruitfully) deployed on a daily basis.

Generally speaking, there are two types of ensemble methods:

• Generate models in sequence. For example, AdaBoost and gradient boosting are such algorithms.
• Generate models in parallel. For …

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