Misclassification minimization based on multiple criteria linear programming

Bo Wang; Yong Shi; Wayne Wei Huang; Guanfeng Liu

doi:10.1109/ICDMW.2014.10

Misclassification minimization based on multiple criteria linear programming

Bo Wang, Yong Shi, Wayne Wei Huang, Guanfeng Liu

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

1 Citation (Scopus)

Abstract

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.

Original language	English
Title of host publication	Proceedings - 14th IEEE International Conference on Data Mining Workshops, ICDMW 2014
Editors	Zhi-Hua Zhou, Wei Wang, Ravi Kumar, Hannu Toivonen, Jian Pei, Joshua Zhexue Huang, Xindong Wu
Place of Publication	Los Alamitos
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	88-92
Number of pages	5
DOIs	https://doi.org/10.1109/ICDMW.2014.10
Publication status	Published - 2014
Externally published	Yes
Event	IEEE International Conference on Data Mining (14th : 2014) - Shenzhen, China Duration: 14 Dec 2014 → 17 Dec 2014

Publication series

Name	IEEE International Conference on Data Mining Workshops, ICDMW
Number	January
Volume	2015-January
ISSN (Print)	2375-9232
ISSN (Electronic)	2375-9259

Conference

Conference	IEEE International Conference on Data Mining (14th : 2014)
Country/Territory	China
City	Shenzhen
Period	14/12/14 → 17/12/14

Keywords

linear approximation
Misclassification minimization
multiple criteria linear programming
Successive linearization algorithm

Access to Document

10.1109/ICDMW.2014.10

Cite this

Wang, B., Shi, Y., Huang, W. W., & Liu, G. (2014). Misclassification minimization based on multiple criteria linear programming. In Z.-H. Zhou, W. Wang, R. Kumar, H. Toivonen, J. Pei, J. Z. Huang, & X. Wu (Eds.), Proceedings - 14th IEEE International Conference on Data Mining Workshops, ICDMW 2014 (pp. 88-92). (IEEE International Conference on Data Mining Workshops, ICDMW; Vol. 2015-January, No. January). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/ICDMW.2014.10

Wang, Bo ; Shi, Yong ; Huang, Wayne Wei et al. / Misclassification minimization based on multiple criteria linear programming. Proceedings - 14th IEEE International Conference on Data Mining Workshops, ICDMW 2014. editor / Zhi-Hua Zhou ; Wei Wang ; Ravi Kumar ; Hannu Toivonen ; Jian Pei ; Joshua Zhexue Huang ; Xindong Wu. Los Alamitos : Institute of Electrical and Electronics Engineers (IEEE), 2014. pp. 88-92 (IEEE International Conference on Data Mining Workshops, ICDMW; January).

@inproceedings{adc9795d5f9e463789fa7ae4cdb6f01a,

title = "Misclassification minimization based on multiple criteria linear programming",

abstract = "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.",

keywords = "linear approximation, Misclassification minimization, multiple criteria linear programming, Successive linearization algorithm",

author = "Bo Wang and Yong Shi and Huang, \{Wayne Wei\} and Guanfeng Liu",

year = "2014",

doi = "10.1109/ICDMW.2014.10",

language = "English",

series = "IEEE International Conference on Data Mining Workshops, ICDMW",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

number = "January",

pages = "88--92",

editor = "Zhi-Hua Zhou and Wei Wang and Ravi Kumar and Hannu Toivonen and Jian Pei and Huang, \{Joshua Zhexue\} and Xindong Wu",

booktitle = "Proceedings - 14th IEEE International Conference on Data Mining Workshops, ICDMW 2014",

address = "United States",

note = "IEEE International Conference on Data Mining (14th : 2014) ; Conference date: 14-12-2014 Through 17-12-2014",

}

Wang, B, Shi, Y, Huang, WW & Liu, G 2014, Misclassification minimization based on multiple criteria linear programming. in Z-H Zhou, W Wang, R Kumar, H Toivonen, J Pei, JZ Huang & X Wu (eds), Proceedings - 14th IEEE International Conference on Data Mining Workshops, ICDMW 2014. IEEE International Conference on Data Mining Workshops, ICDMW, no. January, vol. 2015-January, Institute of Electrical and Electronics Engineers (IEEE), Los Alamitos, pp. 88-92, IEEE International Conference on Data Mining (14th : 2014), Shenzhen, China, 14/12/14. https://doi.org/10.1109/ICDMW.2014.10

Misclassification minimization based on multiple criteria linear programming. / Wang, Bo; Shi, Yong; Huang, Wayne Wei et al.
Proceedings - 14th IEEE International Conference on Data Mining Workshops, ICDMW 2014. ed. / Zhi-Hua Zhou; Wei Wang; Ravi Kumar; Hannu Toivonen; Jian Pei; Joshua Zhexue Huang; Xindong Wu. Los Alamitos: Institute of Electrical and Electronics Engineers (IEEE), 2014. p. 88-92 (IEEE International Conference on Data Mining Workshops, ICDMW; Vol. 2015-January, No. January).

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

TY - GEN

T1 - Misclassification minimization based on multiple criteria linear programming

AU - Wang, Bo

AU - Shi, Yong

AU - Huang, Wayne Wei

AU - Liu, Guanfeng

PY - 2014

Y1 - 2014

N2 - 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.

AB - 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.

KW - linear approximation

KW - Misclassification minimization

KW - multiple criteria linear programming

KW - Successive linearization algorithm

UR - https://www.scopus.com/pages/publications/84936870486

U2 - 10.1109/ICDMW.2014.10

DO - 10.1109/ICDMW.2014.10

M3 - Conference proceeding contribution

T3 - IEEE International Conference on Data Mining Workshops, ICDMW

SP - 88

EP - 92

BT - Proceedings - 14th IEEE International Conference on Data Mining Workshops, ICDMW 2014

A2 - Zhou, Zhi-Hua

A2 - Wang, Wei

A2 - Kumar, Ravi

A2 - Toivonen, Hannu

A2 - Pei, Jian

A2 - Huang, Joshua Zhexue

A2 - Wu, Xindong

PB - Institute of Electrical and Electronics Engineers (IEEE)

CY - Los Alamitos

T2 - IEEE International Conference on Data Mining (14th : 2014)

Y2 - 14 December 2014 through 17 December 2014

ER -

Wang B, Shi Y, Huang WW, Liu G. Misclassification minimization based on multiple criteria linear programming. In Zhou ZH, Wang W, Kumar R, Toivonen H, Pei J, Huang JZ, Wu X, editors, Proceedings - 14th IEEE International Conference on Data Mining Workshops, ICDMW 2014. Los Alamitos: Institute of Electrical and Electronics Engineers (IEEE). 2014. p. 88-92. (IEEE International Conference on Data Mining Workshops, ICDMW; January). doi: 10.1109/ICDMW.2014.10

Misclassification minimization based on multiple criteria linear programming

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