Granular support vector machines with association rules mining for protein homology prediction

Artificial Intelligence in Medicine

Volumn 35, Issue 1-2, 2005, Pages 121-134

  Tang, Yuchun ^a   Jin, Bo ^a   Zhang, Yan Qing ^a  

^a GEORGIA STATE UNIVERSITY   (United States)

Author keywords

Association rules; Binary classification; Granular computing; Granular support vector machines; Protein homology prediction

Indexed keywords

BIOTECHNOLOGY; COMPUTATIONAL METHODS; INFORMATION RETRIEVAL; LEARNING SYSTEMS; PROBLEM SOLVING; VECTOR QUANTIZATION;

ASSOCIATION RULES; BINARY CLASSIFICATION; GRANULAR COMPUTING; GRANULAR SUPPORT VECTOR MACHINES (GSVM); PROTEIN HOMOLOGY PREDICTION;

PROTEINS;

ACCURACY; ALGORITHM; AMINO ACID SEQUENCE; ARTICLE; BIOLOGY; COMPARATIVE STUDY; MATHEMATICAL COMPUTING; MEDICAL INFORMATION; PREDICTION; PRIORITY JOURNAL; SEQUENCE HOMOLOGY; STATISTICAL ANALYSIS; TRAINING;

ALGORITHMS; PROTEIN CONFORMATION; SEQUENCE ANALYSIS, PROTEIN; SEQUENCE HOMOLOGY, AMINO ACID;

EID: 24144442868     PISSN: 09333657     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.artmed.2005.02.003     Document Type: Article

References (22)

1. W.S. Noble Support vector machine applications in computational biology B. Schoelkopf K. Tsuda J.-P. Vert Kernel Methods in Computational Biology 2004 MIT Press 71 92
2. B. Schölkopf, I. Guyon, and J. Weston Statistical Learning and Kernel Methods in Bioinformatics P. Frasconi R. Shamir Artificial Intelligence and Heuristic Methods in Bioinformatics 183 2003 IOS Press Amsterdam 1 21
3. D. Hand, H. Mannila, and P. Smyth Principle of Data Mining 2001 MIT Press Cambridge, London
4. Y.C. Tang, B. Jin, Y. Sun, and Y.-Q. Zhang Granular Support Vector Machines for Medical Binary Classification Problems B. Gary Fogel Proceedings of the IEEE CIBIB 2004 IEEE Computational Intelligence Society Piscataway, HJ 73 78
5. C.J.C. Burges A tutorial on support vector machines for pattern recognition Data Mining Knowledge Disc 2 2 1998 121 167
6. Chin KK, Support vector machines applied to speech pattern classification, Master's thesis, Engineering Department, Cambridge University, 1999.
7. N. Cristianini, and J. Shawe-Taylor An introduction to support vector machines and other Kernel-based learning methods 1999 Cambridge University Press New York
8. S. Gunn Support vector machines for classification and regression, ISIS technical report, Image Speech and Intelligent Systems Group 1998 University of Southampton
9. V. Vapnik Statistical Learning Theory 1998 John Wiley and Sons New York
10. A. Bargiela Granular Computing: an introduction 2002 Kluwer Academic Pub
11. J.T. Yao, and Y.Y. Yao A granular computing approach to machine learning Lipo Wang Saman K. Halgamuge Xin Yao Proceedings of the FSKD'02 2002 Orchid Country Club Singapore 732 736
12. Y.Y. Yao On Modeling data mining with granular computing Proceedings of the COMPSAC 2001 IEEE Computer Society Chicago, IL, USA 638 643
13. R. She, and F. Chen Frequent-subsequence-based prediction of outer membrane proteins Lise Getoor Ted E. Senator Pedro Domingos Christos Faloutsos Proceedings of the SIGKDD'03 2003 ACM press Washington, DC, USA 436 445
14. X. Yin, and J. Han CPAR: classification based on predictive association rules Daniel Barbará Chandrika Kamath Proceedings of the SIAM International Conference on Data Mining 2003 SIAM San Francisco, CA, USA 331 335
15. Y.-Q. Zhang, M.D. Fraser, R.A. Gagliano, and A. Kandel Granular neural networks for numerical-linguistic data fusion and knowledge discovery IEEE Trans Neural Netw 11 3 2000 658 667
16. Bennett KP, Blue J, A support vector machine approach to decision trees, R.P.I math report no. 97-100, Rensselaer Polytechnic Institute, Troy, NY, 1997.
17. H. Yu, J. Yang, and J. Han Classifying large data sets using SVMs with hierarchical clusters Lise Getoor Ted E. Senator Pedro Domingos Christos Faloutsos Proceedings of the SIGKDD'03 2003 ACM press Washington, DC, USA 306 315
18. Ma J, Zhao Y, Ahalt S, OSU SVM Classifier Matlab Toolbox, Available at http://www.ece.osu.edu/∼maj/osu_svm/ (last accessed: 9 April 2005).
19. Chang C-C, Lin C-J, LIBSVM: a library for support vector machines, 2001. Available at http://www.csie.ntu.edu.tw/∼cjlin/libsvm (last accessed 9 April 2005).
20. http://kodiak.cs.cornell.edu/kddcup/index.html (last accessed: 9 April 2005).
21. Caruana R, The PERF Performance Evaluation Code, http://kodiak.cs. cornell.edu/kddcup/software.html (last accessed 9 April 2005).
22. Hsu C-W, Chang C-C, Lin C-J, A practical guide to support vector classification, Available at http://www.csie.ntu.edu.tw/∼cjlin/papers/guide/ guide.pdf (last accessed 9 April 2005).