Ensemble learning: A survey
Omer SagiDepartment of Software and Information Systems Engineering Ben‐Gurion University Beersheba IsraelLior RokachDepartment of Software and Information Systems Engineering Ben‐Gurion University Beersheba Israel
2018en
ABI
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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Cited by 20 references