Faria Nassiri-Mofakham

Work place: Department of Information Technology Engineering, Faculty of Engineering, University of Isfahan, Iran

E-mail: fnasiri@eng.ui.ac.ir


Research Interests: Applied computer science, Computer systems and computational processes, Artificial Intelligence, Theoretical Computer Science


Dr. Faria Nasiri Mofakham is an Assistant Professor in Department of Information Technology at the University of Isfahan (UI). She received her PhD in Computer Engineering from UI (2010).  Her research interests lie under the umbrella of e-Commerce employing any computational theory, method and technology in the field of Computer Science and especially Artificial Intelligence interdisciplined with Sociology, Economics, Psychology, Management, etc.

Author Articles
Performance Analysis of Classification Methods and Alternative Linear Programming Integrated with Fuzzy Delphi Feature Selection

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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