Work place: Department of Management, Faculty of Administrative Sciences and economics, University of Isfahan, Iran
E-mail: bahram1@ase.ui.ac.ir
Website:
Research Interests: Business & Economics & Management
Biography
Dr. Bahram Ranjbarian is a Professor of Marketing at the University of Isfahan and has research interests in consumer behavior. He is currently the Chief Editor of Iranian Journal of Production and Operations Management and also the Assistant Dean of Research Affair in the Faculty of Administrative Sciences and Economics at the University of Isfahan, Iran.
By Bahram Izadi Bahram Ranjbarian Saeedeh Ketabi Faria Nassiri-Mofakham
DOI: https://doi.org/10.5815/ijitcs.2013.10.02, Pub. Date: 8 Sep. 2013
Among various statistical and data mining discriminant analysis proposed so far for group classification, linear programming discriminant analysis have 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, support vector machine, and so on. MDLP is less complex compared to other methods and does not suffer from local optima. However, sometimes classification becomes infeasible due to insufficient data in databases such as in the case of an Internet Service Provider (ISP) small and medium-sized market considered in this research. This study proposes a fuzzy Delphi method to select and gather required data. The results show that the performance of MDLP is better than other methods with respect to correct classification, at least for small and medium-sized datasets.
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