Evaluation of particle swarm optimization based centroid classifier with different distance metrics

2008 IEEE Congress on Evolutionary Computation, CEC 2008

Volumn , Issue , 2008, Pages 2929-2932

  Mohemmed, Ammar W ^a   Zhang, Mengjie ^a  

^a VICTORIA UNIVERSITY OF WELLINGTON   (New Zealand)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFIERS; EVOLUTIONARY ALGORITHMS; LEARNING SYSTEMS; OPTIMIZATION; PROBABILITY DENSITY FUNCTION;

ARITHMETIC MEANS; CLASSIFICATION RESULTS; DATA SETS; DISTANCE FUNCTIONS; DISTANCE METRICS; EUCLIDEAN DISTANCES; MAHALANOBIS DISTANCES; OBJECTIVE FUNCTIONS; PARTICLE SWARMS; SIMULATION RESULTS; TRAINING INSTANCES; WEIGHTED DISTANCES;

PARTICLE SWARM OPTIMIZATION (PSO);

EID: 55749096882     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CEC.2008.4631192     Document Type: Conference Paper

References (15)

1. M. Bicegoa, V. Murinob, M. Pelilloc, and A. Torsello, "Similaritybased pattern recognition," Pattern Recognition, vol. 39 issue 10, pp. 1813-1814, 2006.
2. I. D. Falco, A. D. Cioppa, and E. Tarantino, "Facing classification problems with particle swarm optimization." Applied Soft Computing, vol. 7, pp. 767-783, 2007.
3. Y. M. Y. Hamamoto, "A local mean-based nonparametric classifer," Pattern Recognition Letters, vol. 27, pp. 1151-1159, 2006.
4. J. Kennedy and R. C. Eberhart, "Particle swarm optimization," in Neural Networks, 1995, pp. 1942-1948.
5. I. Levner, "Feature selection and nearest centroid classification for protein mass spectrometry," BMC Bioinformatics, vol. 6, p. 68, 2005.
6. C. Maurice, "The swarm and queen: Towards a deterministic and adaptive particle swarm optimization," IEEE Congress on Evolutionary Computation, vol. 2, 1999, pp. 1951-1957.
7. M. Omran, A. Salman, and A. P. Engelbrecht, "Image classification using particle swarm optimization," in Proceedings of the 4th Asia-Pacific Conference on Simulated Evolution and Learning, 2002, pp. 370-374.
8. R. Paredes and E. Vidal, "Learning weighted metrics to minimize nearest-neighbor classification error," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 28, pp. 1100-1110, July 2006.
9. S. Raudys and A. Jain, "Small sample size effects in statistical pattern recognition: recommendations for practitioners," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 13, pp. 252-264, 1991.
10. S. Shankar and G. Karypis, "Weight adjustment schemes for a centroid based classifier," Department of Computer Science, University of Minnesota, Minneapolis, Minnesota, Tech. Rep. Computer Science Technical Report TR00-035, 2000.
11. T. F. Sousa, A. P. Silva, A. F. Silva, and E. Costa, "Particle swarm based data mining algorithms for classification tasks," Parallel Computing, vol. 30, pp. 767-783, 2004.
12. S. Tan and X. Cheng, An Effective Approach to Enhance Centroid Classifier for Text Categorization. Lecture Notes in Computer Science-Springer Berlin / Heidelberg, 2007, vol. 4702/2007.
13. I. UCI Repository of Machine Learning Databases, University of California, http://archive.ics.uci.edu/ml/datasets.html.
14. D. vander Merwe and A. P. Engelbrecht, "Data clustering using particle swarm optimization," in Proceedings of IEEE Congress on Evolutionary Computation, Canbella. Australia, 2003, pp. 215-220.
15. D. Weinshall, D. W. Jacobsand, and Y. Gdalyahu, "Classifcation in non-metric spaces," Advances in Neural Information Processing Systems, vol. 11, pp. 838-844, 1999.