2011
DOI: 10.1016/j.cor.2010.04.003
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A new mathematical programming approach to multi-group classification problems

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Cited by 17 publications
(10 citation statements)
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References 24 publications
(33 reference statements)
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“…We have implemented a number of literature classifiers to compare the classification rates with our proposed SRW_HB and DR_SRW_HB. The group of classifiers include Naïve Bayes, SMO (support vector machine), Logistic regression, Bagging, Adaboost, NN and three mathematical programming-based multiclass classifiers: HB, Gehrlein (1986) and Bal and Orkcu (2011).…”
Section: Computational Resultsmentioning
confidence: 99%
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“…We have implemented a number of literature classifiers to compare the classification rates with our proposed SRW_HB and DR_SRW_HB. The group of classifiers include Naïve Bayes, SMO (support vector machine), Logistic regression, Bagging, Adaboost, NN and three mathematical programming-based multiclass classifiers: HB, Gehrlein (1986) and Bal and Orkcu (2011).…”
Section: Computational Resultsmentioning
confidence: 99%
“…All the mathematical programming-based classification methods, including SRW_HB, HB, and approaches proposed by Gehrlein (1986) and Bal and Orkcu (2011), are implemented in General Algebraic Modeling System (GAMS) 24.1 (GAMS Development Corporation, 2013) and solved using CPLEX 12.3 solver on a 2.40 GHz speed, 2393 MHz cpu computer system. Optimality gap is set as 0 when solving MILP problems.…”
Section: Computational Resultsmentioning
confidence: 99%
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“…This problem exists in many situations and plays a key role in decision making. 1 ,..., k G G Most researches on DA have focused on the following problem, proposing new mathematical programming models and evaluating the classificatory performance of proposed models against that of the standard parametric classification procedures (Bal and Örkcü, 2010). Sueyoshi (2006) summarized previous research on DA and classified them into four groups as follows.…”
Section: Introductionmentioning
confidence: 99%