Issues in Stacked Generalization
نویسندگان
چکیده
منابع مشابه
Issues in Stacked Generalization
Stacked generalization is a general method of using a high-level model to combine lowerlevel models to achieve greater predictive accuracy. In this paper we address two crucial issues which have been considered to be a `black art' in classi cation tasks ever since the introduction of stacked generalization in 1992 by Wolpert: the type of generalizer that is suitable to derive the higher-level m...
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ژورنال
عنوان ژورنال: Journal of Artificial Intelligence Research
سال: 1999
ISSN: 1076-9757
DOI: 10.1613/jair.594