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摘要
En 中文
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 > Model Combining Technologies > Machine Learning Technologies > Classification
Keyword:
boosting
classifier combination
ensemble models
machine-learning
mixtures of experts
multiple classifier system
random forest
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期刊
IF:
11.7
论文数:
544
被引数:
5.3K
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