A Comparative Study of CCR-(ε-SVR) and CCR-(ν-SVR) Models for Efficiency Prediction of Large Decision Making Units

Mohammadreza Farahmand, Mohammad Ishak Desa, Mehrbakhsh Nilashi


In this paper, we develop CCR-(ε-SVR) and CCR-(ν-SVR) models based on modified parameters for efficiency prediction of large DMUs to improve the accuracy and reduce the computation time using three normalization functions. CCR-(ε-SVR) and CCR-(ν-SVR) are evaluated using large datasets over the three normalization functions. The experimental results of comparisons between CCR-(ε-SVR) and CCR-(ν-SVR) demonstrate that the proposed models can significantly improve the accuracy and reduce the computation time in predicting the efficiency of large DMUs.


Data Envelopment Analysis, Support Vector Regression, Large Decision Making Units, Normalization function

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