Misclassification Minimization Based on Multiple Criteria Linear Programming

Misclassification minimization is an important and interesting topic in classification problem. Obviously, exploring the solution for this topic will benefit to many real life problems, such as credit card clients classification. This paper focuses on misclassification minimization based on multiple...

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Vydané v:IEEE ... International Conference on Data Mining workshops s. 88 - 92
Hlavní autori: Bo Wang, Yong Shi, Huang, Wayne Wei, Guanfeng Liu
Médium: Konferenčný príspevok..
Jazyk:English
Vydavateľské údaje: IEEE 01.12.2014
Predmet:
Credit cards
Educational institutions
linear approximation
Linear programming
Minimization
Misclassification minimization
multiple criteria linear programming
Optimization
Programming
successive linearization algorithm
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ISSN:2375-9232
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Popis
Shrnutí:Misclassification minimization is an important and interesting topic in classification problem. Obviously, exploring the solution for this topic will benefit to many real life problems, such as credit card clients classification. This paper focuses on misclassification minimization based on multiple criteria linear programming (MCLP), proposing two different schemes to minimize the number of misclassified points in original MCLP. Especially, the complementarity is used to construct the first scheme and linear approximation technique is applied to solve it. Furthermore, successive linearization algorithm (SLA) is employed to achieve minimization the second scheme. Finally, numerical experiment tests the effect of this idea.
ISSN:2375-9232
DOI:10.1109/ICDMW.2014.10