1 Ocak 2014 Dergi makalesi Açık Erişim

Yildiz, Olcay Taner

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  "@id": 63613, 
  "@type": "ScholarlyArticle", 
  "creator": [
    {
      "@type": "Person", 
      "name": "Yildiz, Olcay Taner"
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  ], 
  "datePublished": "2014-01-01", 
  "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.", 
  "headline": "On the feature extraction in discrete space", 
  "identifier": 63613, 
  "image": "https://aperta.ulakbim.gov.tr/static/img/logo/aperta_logo_with_icon.svg", 
  "license": "http://www.opendefinition.org/licenses/cc-by", 
  "name": "On the feature extraction in discrete space", 
  "url": "https://aperta.ulakbim.gov.tr/record/63613"
}