Effective pruning method for a multiple classifier system based on self-generating neural networks

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 2714, Issue , 2003, Pages 11-18

  Inoue, Hirotaka ^a   Narihisa, Hiroyuki ^b  

^a KURE NATIONAL COLLEGE OF TECHNOLOGY   (Japan)

^b OKAYAMA UNIVERSITY OF SCIENCE   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

NEAREST NEIGHBOR SEARCH;

CLASSIFICATION ACCURACY; COMPUTATIONAL COSTS; FAST LEARNING; K-NEAREST NEIGHBOR METHOD; MULTIPLE CLASSIFIER SYSTEMS; PRUNING METHODS; SELF-GENERATING NEURAL NETWORKS;

NEURAL NETWORKS;

EID: 35248878650     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-44989-2_2     Document Type: Article

References (13)

1. J. Han and M. Kamber. Data Mining: Concepts and Techniques. Morgan Kaufmann Publishers, San Francisco, CA, 2000.
2. J. R. Quinlan. Bagging, Boosting, and C4.5. In Proceedings of the Thirteenth National Conference on Artificial Intelligence, pages 725-730, Portland, OR, 1996.
3. G. Rätsch, T. Onoda, and K.-R. Müller. Soft margins for AdaBoost. Machine Learning, 42(3):287-320, 2001.
4. C. M. Bishop. Neural Networks for Pattern Recognition. Oxford University Press, New York, 1995.
5. R. O. Duda, P. E. Hart, and D. G. Stork. Pattern Classification. John Wiley & Sons Inc., New York, 2nd ed., 2000.
6. W. X. Wen, A. Jennings, and H. Liu. Learning a neural tree. In the International Joint Conference on Neural Networks, Beijing, China, 1992. This paper is available at ftp://ftp.cis.ohio-state.edu/pub/neuroprose/wen.sgnt-learn.pa.Z.
7. T. Kohonen. Self-Organizing Maps. Springer-Verlag, Berlin, 1995.
8. H. Inoue and H. Narihisa. Improving generalization ability of self-generating neural networks through ensemble averaging. In T. Terano, H. Liu, and A. L P. Chen, eds, The Fourth Pacific-Asia Conference on Knowledge Discovery and Data Mining, vol. 1805 of LNAI, pages 177-180, Springer-Verlag, 2000.
9. M. Stone. Cross-validation: A review. Math. Operationsforsch. Statist., Ser. Statistics, 9(1):127-139, 1978.
10. L. Breiman. Bagging predictors. Machine Learning, 24:123-140, 1996.
11. J. R. Quinlan. C4.5: Programs for Machine Learning. Morgan Kaufmann, San Mateo, CA, USA, 1993.
12. C.L. Blake and C.J. Merz. UCI repository of machine learning databases, University of California, Irvine, Dept of Information and Computer Science, 1998. Datasets is available at http://www.ics.uci.edu/~mlearn/HLRepository.html.
13. E. A. Patrick and F. P. Fischer. A generalized k-nearest neighbor rule. Information and Control, 16(2):128-152, 1970.