For questions related to ensemble learning, which refers to machine learning techniques where multiple models (e.g. a neural network and a decision tree) are trained and their predictions are combined to solve the same problem. Bagging and boosting are two popular ensemble learning techniques.
Questions tagged [ensemble-learning]
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How can an ensemble be more accurate than the best base classifier in that ensemble?
BACKGROUND: Ensemble classifiers are said to reduce bias by taking an "average" of predictions of several base classifiers that comprise the ensemble. However, I am uncertain if this necessarily means that they can increase accuracy. My intuition…
Snehal Patel
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