A New Approach Using Data Envelopment Analysis for Ranking Classification Algorithms

Abstract

Problem statement: A variety of methods and algorithms for classification problems have been developed recently. But the main question is that how to select an appropriate and effective classification algorithm. This has always been an important and difficult issue. Approach: Since the classification algorithm selection task needs to examine more than one criterion such as accuracy and computational time, it can be modeled and also ranked by Data Envelopment Analysis (DEA) technique. Results: In this study, 44 standard databases were modeled by 7 famous classification algorithms and we have examined them by accreditation method. Conclusion/Recommendation: The results indicate that Data Envelopment Analysis (DEA) is an appropriate tool for evaluating classification algorithms.