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:: جلد 4، شماره 1 - ( 3-1392 ) ::
جلد 4 شماره 1 صفحات 55-74 برگشت به فهرست نسخه ها
Multi-Group Classification Using Interval Linea rProgramming
چکیده:   (13189 مشاهده)

  Among various statistical and data mining discriminant analysis proposed so far for group classification, linear programming discriminant analysis has recently attracted the researchers’ interest. This study evaluates multi-group discriminant linear programming (MDLP) for classification problems against well-known methods such as neural networks and support vector machine. MDLP is less complicated as compared to other methods and does not suffer from having local optima. This study also proposes a fuzzy Delphi method to select and gather the required data, when databases suffer from deficient data. In addition, to absorb the uncertainty infused to collecting data, interval MDLP (IMDLP) is developed. The results show that the performance of MDLP and specially IMDLP is better than conventional classification methods with respect to correct classification, at least for small and medium-size datasets.

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نوع مطالعه: پژوهشی |
دریافت: 1393/2/4 | پذیرش: 1393/2/4 | انتشار: 1393/2/4
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جلد 4، شماره 1 - ( 3-1392 ) برگشت به فهرست نسخه ها
مجله انجمن ایرانی تحقیق در عملیات Iranian Journal of Operations Research
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