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
Keywords
Ensemble learningComputer scienceMachine learningArtificial intelligenceField (mathematics)Ensemble forecastingData scienceMathematics
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Publication Info
- Year
- 2018
- Type
- article
- Volume
- 8
- Issue
- 4
- Citations
- 2796
- Access
- Closed
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Cite This
Omer Sagi,
Lior Rokach
(2018).
Ensemble learning: A survey.
Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery
, 8
(4)
.
https://doi.org/10.1002/widm.1249
Identifiers
- DOI
- 10.1002/widm.1249