Adaptive Local Hyperplane Classification

Publisher:
Elsevier BV
Publication Type:
Journal Article
Citation:
Neurocomputing, 2008, 71 (13-15), pp. 3001 - 3004
Issue Date:
2008-01
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In this paper, a novel classifier, called adaptive local hyperplane, is proposed for pattern classification. The experimental results on 11 real data sets demonstrate that the proposed classifier outperforms, on average, all the other seven benchmarking classifiers. In particular, it is the best classifier in 10 out of 11 data sets, and it is the close second best for just one data set.
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