« Previous
Next »
Artificial Intelligence in Medicine
Volume 35, Issue 1
, Pages 121-134
, September 2005
Granular support vector machines with association rules mining for protein homology prediction
References
- . Support vector machine applications in computational biology. In: Schoelkopf B, Tsuda K, Vert J-P editor. Kernel Methods in Computational Biology. MIT Press; 2004;p. 71–92
- . Statistical Learning and Kernel Methods in Bioinformatics. In: Frasconi P, Shamir R editor. Artificial Intelligence and Heuristic Methods in Bioinformatics 183. Amsterdam: IOS Press; 2003;p. 1–21
- . Principle of Data Mining. Cambridge, London: MIT Press; 2001;
- . Granular Support Vector Machines for Medical Binary Classification Problems. In: Gary B, Fogel editor. Proceedings of the IEEE CIBIB. Piscataway, HJ: IEEE Computational Intelligence Society; 2004;p. 73–78
- . A tutorial on support vector machines for pattern recognition. Data Mining Knowledge Disc. 1998;2(2):121–167
- Chin KK, Support vector machines applied to speech pattern classification, Master's thesis, Engineering Department, Cambridge University, 1999.
- . An introduction to support vector machines and other Kernel-based learning methods. New York: Cambridge University Press; 1999;
- . Support vector machines for classification and regression, ISIS technical report, Image Speech and Intelligent Systems Group. University of Southampton; 1998;
- . Statistical Learning Theory. New York: John Wiley and Sons; 1998;
- . Granular Computing: an introduction. Kluwer Academic Pub; 2002;
- . A granular computing approach to machine learning. In: Wang Lipo, Halgamuge Saman K, Yao Xin editor. Proceedings of the FSKD’02. Singapore: Orchid Country Club; 2002;p. 732–736
- . On Modeling data mining with granular computing. In: Proceedings of the COMPSAC. Chicago, IL, USA: IEEE Computer Society; 2001;p. 638–643
- . Frequent-subsequence-based prediction of outer membrane proteins. In: Getoor Lise, Senator Ted E, Domingos Pedro, Faloutsos Christos editor. Proceedings of the SIGKDD’03. Washington, DC, USA: ACM press; 2003;p. 436–445
- . CPAR: classification based on predictive association rules. In: Barbará Daniel, Kamath Chandrika editor. Proceedings of the SIAM International Conference on Data Mining. San Francisco, CA, USA: SIAM; 2003;p. 331–335
- . Granular neural networks for numerical-linguistic data fusion and knowledge discovery. IEEE Trans Neural Netw. 2000;11(3):658–667
- 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.
- . Classifying large data sets using SVMs with hierarchical clusters. In: Getoor Lise, Senator Ted E, Domingos Pedro, Faloutsos Christos editor. Proceedings of the SIGKDD’03. Washington, DC, USA: ACM press; 2003;p. 306–315
- 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).
- 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).
- http://kodiak.cs.cornell.edu/kddcup/index.html (last accessed: 9 April 2005).
- Caruana R, The PERF Performance Evaluation Code, http://kodiak.cs.cornell.edu/kddcup/software.html (last accessed 9 April 2005).
- 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).
PII: S0933-3657(05)00054-0
doi: 10.1016/j.artmed.2005.02.003
© 2005 Elsevier B.V. All rights reserved.
« Previous
Next »
Artificial Intelligence in Medicine
Volume 35, Issue 1
, Pages 121-134
, September 2005
