Ensembling neural networks: Many could be better than all
نویسندگان
چکیده
منابع مشابه
Ensembling neural networks: Many could be better than all
Neural network ensemble is a learning paradigm where many neural networks are jointly used to solve a problem. In this paper, the relationship between the ensemble and its component neural networks is analyzed from the context of both regression and classification, which reveals that it may be better to ensemble many instead of all of the neural networks at hand. This result is interesting beca...
متن کاملCorrigendum to "Ensembling neural networks: Many could be better than all" [Artificial Intelligence 137 (1-2) (2002) 239-263]
In 2002, we published in Artificial Intelligence an extension [1] of a paper we presented at IJCAI-01 [2]. In Section 2 of the IJCAI-01 paper [2] and in Section 2.1 of the AIJ paper [1], we presented a criterion for selecting a subset of an ensemble of neural networks that could yield better performance than using all members of the ensemble for regression. The fundamental motivation for this c...
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ژورنال
عنوان ژورنال: Artificial Intelligence
سال: 2002
ISSN: 0004-3702
DOI: 10.1016/s0004-3702(02)00190-x