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Fuzzy classification using the data envelopment analysis
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DOI：10.1016/j.knosys.2012.03.007.png)
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Abstract
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We develop a fuzzy classification system using data envelopment analysis (DEA) and illustrate its application using a simple graduate admissions decision-making problem. Using simulated and real-world datasets, we benchmark the proposed DEA based fuzzy classification system (DBFCS) with the adaptive neuro fuzzy inference system (ANFIS), fuzzy rule based classification system (FRCS) and logistic regression (Logit); and illustrate that the DBFCS outperforms all competing models. (C) 2012 Elsevier B.V. All rights reserved.
Keywords:
Fuzzy membership functions
Fuzzy neural networks
Data envelopment analysis
Fuzzy classification
Data mining
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