The Reconstructed Heterogeneity to Enhance Ensemble Neural Network for Large Data
This paper presents an enhanced approach for ensemble multi classifier of Artificial Neural Networks (ANN). The motivation of this study is to improve the ANN capability and performance using reconstructed heterogeneous if the homogenous classifiers are deployed. The clusters set are partitioned int...
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主要な著者: | , , |
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フォーマット: | Book Section |
言語: | English English |
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Springer Cham
2016
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オンライン・アクセス: | http://eprints.unisza.edu.my/3382/1/FH05-FIK-17-09478.pdf http://eprints.unisza.edu.my/3382/2/FH05-FIK-17-09479.pdf http://eprints.unisza.edu.my/3382/ |
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