Data classification with a relaxed model of variable kernel density estimation

Proceedings of the International Joint Conference on Neural Networks

Volumn 5, Issue , 2005, Pages 2831-2836

  Oyang, Yen Jen ^a   Ou, Yu Yen ^a   Hwang, Shien Ching ^a   Chen, Chien Yu ^b   Chang, Darby Tien Hau ^a  

^a NATIONAL TAIWAN UNIVERSITY   (Taiwan)

^b YUAN ZE UNIVERSITY   (Taiwan)

Author keywords

Data classification; Kernel density estimation; Radial basis function; RBF network; Variable kernel density estimation

Indexed keywords

CLASSIFICATION (OF INFORMATION); COMPUTER VISION; CONVERGENCE OF NUMERICAL METHODS; ERROR ANALYSIS; LEARNING SYSTEMS; PROBLEM SOLVING; RADIAL BASIS FUNCTION NETWORKS;

DATA CLASSIFICATION; INTEGRATED MEAN SQUARE ERROR (IMSE); KERNEL DENSITY ESTIMATION; MEAN SQUARE ERROR (MSE);

DATA PROCESSING;

EID: 33750102677     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IJCNN.2005.1556374     Document Type: Conference Paper

References (23)

1. I. S. Abramson, "On Bandwidth Variation in Kernel Estimates - A Square Root Law," The Annals of Statistics, vol. 10, no. 4, pp. 1217-1223, 1982.
2. C. M. Bishop, "Improving the generalization properties of radial basis function neural networks," Neural Computation, vol. 3, no. 4, pp. 579-5881, 1991.
3. M. J. Black, D. J. Fleet, and Y. Yacoob, "Robustly estimating changes in image appearance," Computer Vision and Image Understanding, vol. 78, no. 1, pp. 8-31, 2000.
4. C. L. Blake and C. J. Merz, "UCI repository of machine learning databases," Technical report, University of California, Department of Information and Computer Science, Irvine, CA, 1998.
5. L. Breiman, W. Meisel, and E. Purcell, "Variable kernel estimates of multivariate densities," Technometrics, vol. 19, pp. 135-144, 1977.
6. D. Ti.-H. Chang, C.-Y. Chen, W.-C. Chung, Y.-J. Oyang, H.-F. Juan, and H.-C. Huang, "ProteMiner-SSM: A Web Server for Identifying Possible Protein-Ligand Interactions Based on Analysis of Protein Tertiary Substructures," Nucleic Acids Research, vol. 32 (Web Server issue), W76-W82, 2004.
7. C. Cortes and V. Vapnik. "Support-vector network," Machine Learning, vol. 20, pp. 273-297, 1995.
8. M. N. Dailey, G. W. Cottrell, and T. A. Busey, "Facial memory is kernel density estimation (almost)," Advances in Neural Information Processing Systems, vol. 11, pp. 24-30, 1998.
9. G. L. David, "Similarity metric learning for a variable-kernel classifier," Neural Computation, vol. 7, no. 1, pp. 72-85, 1995.
10. L. Devroye. A Course in Density Estimation. In Birkhauser:Boston MA, 1987.
11. C. W. Hsu and C. J. Lin. "A comparison of methods for multi-class support vector machines," IEEE Transactions on Neural Networks, vol. 13, no. 2, pp. 415-425, 2002.
12. Y. S. Hwang and S. Y. Bang, "An efficient method to construct a radial basis function neural network classifier," Neural Networks, vol. 10, no. 8, pp. 1495-1503, 1997.
13. J. Moody and C. J. Darken, "Fast learning in networks of locally-tuned processing units," Neural Computation, vol. 1, no. 2, pp. 281-294, 1989.
14. M. Musavi, W. Ahmed, K. Chan, K. Faris, and D. Hummels, "On the training of radial basis function classifiers," Neural Networks, vol. 5, no. 4, pp. 595-603, 1992.
15. M. J. L. Orr, "Regularisation in the selection of radial basis function centres," Neural Computation, vol. 7, no. 3, pp. 606-623, 1995.
16. M. J. L. Orr, "Introduction to radial basis function networks," Technical report, Center for Cognitive Science, University of Edinburgh, 1996.
17. M. J. Orr, "Optimising the widths of radial basis function," Proceedings of the Fifth Brazilian Symposium on Neural Networks, pp. 26-29, 1998.
18. Y.-J. Oyang, S.-C. Hwang, Y.-Y. Ou, C.-Y. Chen, and Z.-W. Chen, "A Novel Learning Algorithm for Data Classification with Radial Basis Function Networks," Proceedings of 9th International Conference on Neural Information Processing, pp. 1021-1026, 2002.
19. Y.-J. Oyang, S.-C. Hwang, Y.-Y. Ou, C.-Y. Chen, and Z.-W. Chen, "Data Classification with Radial Basis Function Networks Based on a Novel Kernel Density Estimation Algorithm", IEEE Transactions on Neural Networks, vol. 16, no. 1, pp. 225-236, 2005.
20. Y.-Y. Ou, C.-Y. Chen, Y.-J. Oyang, "Data Classification Based on Radial Basis Function Networks Constructed with An Incremental Hierarchical Clustering Algorithm", To appear in Proceedings of International Joint Conference on Neural Networks, 2005.
21. S. R. Sain and D. W. Scott, "Zero-Bias Locally Adaptive Density Estimators," Scandinavian Journal of Statistics, vol. 29, no. 3, pp. 441, 2002.
22. B. W. Silverman, Density Estimation for Statistics and Data Analysis, Chapman and Hall, London, 1986.
23. G. R. Terrell and D. W. Scott, "Variable kernel density estimation," The Annals of Statistics, no. 20, pp. 1236-1265, 1992.