Extreme learning machine for multi-categories classification applications

Proceedings of the International Joint Conference on Neural Networks

Volumn , Issue , 2008, Pages 1709-1713

  Rong, Hai Jun ^a   Huang, Guang Bin ^a   Ong, Yew Soon ^b  

^a NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

^b NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

Author keywords

[No Author keywords available]

Indexed keywords

BENCHMARKING; CLASSIFIERS; KETONES; NEURAL NETWORKS;

BENCHMARK PROBLEMS; BINARY CLASSIFIERS; CLASS PATTERNS; COMPUTATION BURDENS; EXTREME LEARNING MACHINES; HIDDEN NODES; PATTERN CLASSES; SIMULATION RESULTS;

LEARNING SYSTEMS;

EID: 56349171345     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IJCNN.2008.4634028     Document Type: Conference Paper

References (16)

1. G.-B. Huang, Q.-Y. Zhu, and C-K. Siew, "Extreme learning machine: A new learning scheme of feedforward neural networks," in Proceedings of International Joint Conference on Neural Networks (IJCNN2004), vol. 2, (Budapest, Hungary), pp. 985-990, 25-29 July, 2004.
2. G.-B. Huang, Q.-Y. Zhu, K. Z. Mao, C.-K. Siew, P. Saratchandran, and N. Sundararajan, "Can threshold networks be trained directly?," IEEE Transactions on Circuits and Systems II, vol. 53, no. 3, pp. 187-191, 2006.
3. G.-B. Huang, Q.-Y. Zhu, and C.-K. Siew, "Extreme learning machine: Theorey and applications," Neurocomputing, vol. 70, pp. 489-501, 2006.
4. N.-Y. Liang, P. Saratchandran, G.-B. Huang, and N. Sundararajan, "Classification of mental tasks from EEG signals using extreme learning machine," International Journal of Neural Systems, vol. 16, no. 1, pp. 29-38, 2006.
5. S. D. Handoko, K. C. Keong, Y.-S. Ong, G. L. Zhang, and V. Brusic, "Extreme learning machine for predicting HLA-peptide binding," Lecture Notes in Computer Science, vol. 3973, pp. 716-721, 2006.
6. J.-X. Xu, W. Wang, J. C. H. Goh, and G. Lee, "Internal model approach for gait modeling and classification," in the 27th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS), (Shanghai, China), September 1-4, 2005.
7. C.-W. T. Yeu, M.-H. Lim, G.-B. Huang, A. Agarwal, and Y.-S. Ong, "A new machine learning paradigm for terrain reconstruction," IEEE Geoscience And Remote Sensing Letters, vol. 3, no. 3, pp. 382-386, 2006.
8. G.-B. Huang, Q.-Y. Zhu, and C.-K. Siew, "Real-time learning capability of neural networks," IEEE Transactions on Neural Networks, vol. 17, no. 4, pp. 863-878, 2006.
9. J. Kim, H. Shin, Y. Lee, and M. Lee, "Algorithm for classifying arrhythmia using extreme learning machine and principal component analysis," in Proceedings of the 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS), pp. 3257-3260, Lyon, France, August 23-26, 2007.
10. H. S. Shin and M. Lee, "Activity of daily living classification with acceleration signal using extreme learning machine," in The International Conference on Electrical Engineering 2007 (ICEE2007), Hong Kong, July 8-12, 2007.
11. G. Wang, Y. Zhao, and D. Wang, "A protein secondary structure prediction, framework based on the extreme learning machine," Neurocomputing (in press), 2008.
12. G.-B. Huang, L. Chen, and C.-K. Siew, "Universal approximation using incremental constructive feedforward networks with random hidden nodes," IEEE Transactions on neural networks, vol. 17, no. 4, pp. 879-892, 2006.
13. G.-B. Huang and L. Chen, "Convex incremental extreme learning machine," Neurocomputing, vol. 70, pp. 3056-3062, 2007.
14. C. Blake and C. Merz, "UCI repository of machine learning databases [online]," in http://www.ics.uci.edu/mlearn/MLRepository.html, (Department of Information and Computer Sciences, University of California, Irvine, USA), 1998.
15. C. Rao and S. K. Mitra, Generalized Inverse of Matrices and Its Applications. John Wiley & Sons, Inc, New York, 1971.
16. E. L. Allwein, R. E. Schapire, and Y. Singer, "Reducing multiclass to binary: a unifying approach for margin classifiers," The Journal of Machine Learning Research, vol. 1, pp. 113-141, 2001.