1 Ocak 2014 Dergi makalesi Açık Erişim

Yildiz, Olcay Taner

Citation Style Language JSON

{
  "DOI": "10.1016/j.patcog.2013.11.023", 
  "abstract": "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.", 
  "author": [
    {
      "family": "Yildiz", 
      "given": " Olcay Taner"
    }
  ], 
  "container_title": "PATTERN RECOGNITION", 
  "id": "63613", 
  "issue": "5", 
  "issued": {
    "date-parts": [
      [
        2014, 
        1, 
        1
      ]
    ]
  }, 
  "page": "1988-1993", 
  "title": "On the feature extraction in discrete space", 
  "type": "article-journal", 
  "volume": "47"
}