Soft-voting classification using locally linear reconstruction

Proceedings - 2011 7th International Conference on Computational Intelligence and Security, CIS 2011

Volumn , Issue , 2011, Pages 1211-1214

  Tian, Xiaohui ^a   Wang, Rong ^a  

^a WEINAN NORMAL UNIVERSITY   (China)

Author keywords

Locally linear reconstruction; Soft voting; Supervised classification

Indexed keywords

BENCHMARK DATA; DATA POINTS; DIMENSIONALITY REDUCTION METHOD; K-NEAREST NEIGHBOR CLASSIFIER; LINEAR RECONSTRUCTION; LOCALLY LINEAR EMBEDDING; SOFT VOTING; SUPERVISED CLASSIFICATION; SUPERVISED CLASSIFIERS; TEST SAMPLES; TIME COMPLEXITY; TRAINING SAMPLE; VERY LARGE DATUM;

COMPUTATIONAL METHODS;

ARTIFICIAL INTELLIGENCE;

EID: 84863046677     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CIS.2011.268     Document Type: Conference Paper

References (10)

1. G. A. christopher, W.M. Andrew, and S. Stefan, "LocallyWeighted Learning," Kernel Smoothing, Artificial Intelligence Review, vol. 11, p. 11-73, 1997.
2. T. Cover and P. Hart, "Nearest neighbor pattern classification, " IEEE Transactions on Information Theory, vol. IT-IS, p. 21-27, 1967.
3. S. Chopra, R. Hadsell, and Y. LeCun, "Learning a similiarty metric discriminatively, with application to face verification," In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR-05), San Diego, CA, 2005.
4. C. Domeniconi, D. Gunopulos, and J. Peng, "Large margin nearest neighbor classifiers," IEEE Transactions on Neural Networks, vol. 16, no. 4, p. 899-909, 2005.
5. J. Goldberger, S. Roweis, G Hinton, and R. Salakhutdinov, "Neighbourhood components analysis," In L. K. Saul, Y. Weiss, and L. Bottou, editors, Advances in Neural Information Processing Systems 17, p. 513-520, Cambridge, MA, 2005. MIT Press.
6. S. Shalev-Shwartz, Y. Singer, and A. Y. Ng, "Online and batch learning of pseudo-metrics," In Proceedings of the 21 st International Conference on Machine Learning, Banff, Canada, 2004.
7. N. Shental, T. Hertz, D. Weinshall, and M. Pavel. Adjustment learning and relevant component analysis. In Proceedings of the Seventh European Conference on Computer Vision (ECCV-02), vol 4, p. 776-792, London, UK, 2002. Springer-Verlag.
8. P. Kang and S. Cho, "Locally linear reconstruction for instance-based learning," Pattern Recognition, vol. 41, no. 11, p. 3507-3518, 2008.
9. A. Frank and A. Asuncion, UCI Machine Learning Repository [http://archive.ics.uci.edu/ml]. Irvine, CA: University of California, School of Information and Computer Science, 2010.
10. L. Saul and S. Roweis, "Think globally, fit Locally: Unsupervised learning of low dimensional manifolds," Journal of Machine Learning Research, vol. 4, p. 119-155, 2003.