A class of classification and regression methods by multiobjective programming

Dongling ZHANG , Yong SHI , Yingjie TIAN , Meihong ZHU

Front. Comput. Sci. ›› 2009, Vol. 3 ›› Issue (2) : 192 -204.

PDF (827KB)
Front. Comput. Sci. ›› 2009, Vol. 3 ›› Issue (2) : 192 -204. DOI: 10.1007/s11704-009-0026-2
REVIEW ARTICLE

A class of classification and regression methods by multiobjective programming

Author information +
History +
PDF (827KB)

Abstract

An extensive review for the recent developments of multiple criteria linear programming data mining models is provided in this paper. These researches, which include classification and regression methods, are introduced in a systematic way. Some applications of these methods to real-world problems are also involved in this paper. This paper is a summary and reference of multiple criteria linear programming methods that might be helpful for researchers and applications in data mining.

Keywords

multiple criteria linear programming / data mining / classification / regression

Cite this article

Download citation ▾
Dongling ZHANG, Yong SHI, Yingjie TIAN, Meihong ZHU. A class of classification and regression methods by multiobjective programming. Front. Comput. Sci., 2009, 3(2): 192-204 DOI:10.1007/s11704-009-0026-2

登录浏览全文

4963

注册一个新账户 忘记密码

References

[1]

Shi Y. Data mining. In: M. Zeleny (Ed.), IEBM Handbook of Information Technology in Business. England: International Thomson Publishing, 2002, 490-495

[2]

Han J, Kamber M. Data Mining: Concepts and Techniques. San Francisco, California : Morgan Kaufmann Publishers, 2001

[3]

Kou G, Peng Y, Shi Y. Multiple criteria linear programming to data mining: models, algorithm designs and software developments. Optimization Methods and Software. 2003, 18(4): 453-473

[4]

Fox J. Multiple and generalized nonparametric regression. Sage university papers series on Quantitative Applications in the Social Sciences. CA: Sage. Thousand Oaks, 2000, 07-131

[5]

Zhang D, Tian Y, Shi Y. A Regression Method by MCLP. In: Proceeding of Conference on Multi-criteria Decision Making 2008. 2008, Working Paper

[6]

Zhang D, Tian Y, Shi Y. Kernel-based estimation method. In: Proceedings of International Conference on Web Intelligence (WI08) and International Conference on Intelligent Agent Technology (IAT08), To appear

[7]

Freed N, Glover F. Simple but powerful goal programming models for discriminant problems. European Journal of Operational Research, 1981, 7: 44-60

[8]

Freed N, Glover F. Evaluating alternative linear programming models to solve the two-group discriminant problem. Decision Sciences. 1986, 17: 151-162

[9]

Shi Y, Wise M, Luo M, . data mining in credit card portfolio management: a multiple criteria decision making approach. In: Advance in Multiple Criteria Decision Making in the New Millennium. Berlin: Springer, 2001, 427-436

[10]

Kou G. Multi-class multi-criteria mathematical programming and its applications in large scale data mining problems. PhD Dissertation for the Doctoral Degree. University of Nebraska Omaha, 2006

[11]

Zheng J, Zhuang W, Yan N, . Classification of HIV-1 mediated neuronal dendritic and synaptic damage using multiple criteria linear programming. Neuroinformatics, 2003, 2(3): 303-326

[12]

Kwak W, Shi Y, Cheh.J J. Firm bankruptcy prediction using multiple criteria linear programming data mining approach. Advances in Investment Analysis and Portfolio Management, 2005

[13]

Kou G, Peng Y, Yan N, . Network intrusion detection by using multiple-criteria linear programming. In: Proceedings of 2004 International Conference on Service Systems and Service Management. Beijing, 2004, 806-809

[14]

Zhang P, Dai J R. Multiple-criteria linear programming for VIP e-mail behavior analysis. In: Proceedings of 7th international conference on data mining workshops. (ICDMW2007). 2007, 289-296

[15]

Zhang P, Zhang J L, Shi Y. A new multi-criteria quadraticprogramming linear classification model for VIP e-mail analysis. In: Proceedings of ICCS 2007, Part II. Springer, 2007, (4488), 499-502

[16]

Shi Y, Liu R, Yan N, . A family of multiple objective optimization based data mining methods, Working Paper

[17]

Zhang Z, Zhang D, Tian Y, . Kernel-based multiple criteria linear program. In: Proceeding of Conference on Multi-criteria Decision Making 2008. 2008, Working Paper

[18]

Zhang D, Tian Y, Shi Y. Knowledge-incorporated MCLP Classifier. In: Proceeding of Conference on Multi-criteria Decision Making 2008. 2008, Working Paper

[19]

Deng N, Tian Y. New Approach in Data Mining—Support Vector Machine. Beijing: Science Publication, 2004

[20]

Downs T, Gates K E,Masters A. Exact simplification of support vector solutions. Journal of Machine Learning Research, 2002, 2: 293-297

[21]

Fung G, Mangasarian O L, Shavlik J. Knowledge-based support vector machine classifiers. In: Proceedings of NIPS 2002. Vancouver, 2002, 9-14

[22]

Bi J, Bennett K P. Duality, geometry and support vector regression. In: Advances in Neural Information Processing Systems. Cambridge: MIT Press. 2002, 593-600

[23]

Smola A J, Scholkopf B. A tutorial on SVR. Statistics and Computing. Netherlands: Kluwer Academic Publishers, 2004, 199-222

[24]

Meng D, Xu C, Jing W. A new approach for regression. Visual Regression Approach. CIS 2005, Part I, LNAI 3801. Springer-Verlag, 2005, 139-144

[25]

Fradkin D, Madigan D. Experiments with random projections for machine learning. In: Proceedings of International Conference on Knowledge Discovery and Data Mining.ACM, 2003, 517-522

[26]

Balcan M F, Blum A, Vempala S. Kernels as features: on kernels, margins, and low-dimensional mappings. Machine Learning, 2006, 65(1): 79-94

RIGHTS & PERMISSIONS

Higher Education Press and Springer-Verlag Berlin Heidelberg

AI Summary AI Mindmap
PDF (827KB)

1001

Accesses

0

Citation

Detail

Sections
Recommended

AI思维导图

/