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A class of classification and regression methods by multiobjective programming

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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.

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References

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

    Google Scholar 

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

    Google Scholar 

  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

    Article  MATH  MathSciNet  Google Scholar 

  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

    Google Scholar 

  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

    Article  MATH  Google Scholar 

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

    Article  Google Scholar 

  9. Shi Y, Wise M, Luo M, et al. 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

    Google Scholar 

  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, et al. Classification of HIV-1 mediated neuronal dendritic and synaptic damage using multiple criteria linear programming. Neuroinformatics, 2003, 2(3): 303–326

    Article  Google Scholar 

  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, et al. 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 quadratic-programming 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, et al. A family of multiple objective optimization based data mining methods, Working Paper

  17. Zhang Z, Zhang D, Tian Y, et al. 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

    Google Scholar 

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

    Article  MATH  Google Scholar 

  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

    Google Scholar 

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

    Google Scholar 

  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

    Article  Google Scholar 

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Authors and Affiliations

  1. Research Center on Fictitious Economy and Data Sciences, Chinese Academy of Sciences, Beijing, 100080, China

    Dongling Zhang, Yong Shi, Yingjie Tian & Meihong Zhu

  2. College of Information Science and Technology, University of Nebraska at Omaha, Omaha, NE, 68132, USA

    Yong Shi

  3. School of Computer Science, University of Science and Technology, Beijing, 100083, China

    Dongling Zhang

  4. Management School, Graduate University of Chinese Academy of Sciences, Beijing, 100080, China

    Dongling Zhang, Yong Shi & Meihong Zhu

  5. School of Statistics, Capital University of Economics and Business, Beijing, 100070, China

    Meihong Zhu

Authors
  1. Dongling Zhang
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  2. Yong Shi
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  3. Yingjie Tian
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  4. Meihong Zhu
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Corresponding author

Correspondence to Yong Shi.

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Zhang, D., Shi, Y., Tian, Y. et al. A class of classification and regression methods by multiobjective programming. Front. Comput. Sci. China 3, 192–204 (2009). https://doi.org/10.1007/s11704-009-0026-2

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  • DOI: https://doi.org/10.1007/s11704-009-0026-2

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