Dergi makalesi Açık Erişim
Yildiz, Olcay Taner
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"description": "In many pattern recognition applications, feature space expansion is a key step for improving the performance of the classifier. In this paper, we (i) expand the discrete feature space by generating all orderings of values of k discrete attributes exhaustively, (ii) modify the well-known decision tree and rule induction classifiers (ID3, Quilan, 1986 [1] and Ripper, Cohen, 1995 [2]) using these orderings as the new attributes. Our simulation results on 15 datasets from UCI repository [3] show that the novel classifiers perform better than the proper ones in terms of error rate and complexity. (C) 2013 Elsevier Ltd. All rights reserved.",
"doi": "10.1016/j.patcog.2013.11.023",
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"issue": "5",
"pages": "1988-1993",
"title": "PATTERN RECOGNITION",
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"title": "On the feature extraction in discrete space"
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