Abstract
Ensemble methods are considered the state‐of‐the art solution for many machine learning challenges. Such methods improve the predictive performance of a single model by training multiple models and combining their predictions. This paper introduce the concept of ensemble learning, reviews traditional, novel and state‐of‐the‐art ensemble methods and discusses current challenges and trends in the field.This article is categorized under:

Algorithmic Development > Ensemble Methods
Technologies > Machine Learning
Technologies > Classification
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Published
Feb 27, 2018
Vol/Issue
8(4)
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Cite This Article
Omer Sagi, Lior Rokach (2018). Ensemble learning: A survey. WIREs Data Mining and Knowledge Discovery, 8(4). https://doi.org/10.1002/widm.1249
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