To combine steady-state genetic algorithm and ensemble learning for data clustering

Pattern Recognition Letters

Volumn 29, Issue 9, 2008, Pages 1416-1423

  Hong, Yi ^a   Kwong, Sam ^a  

^a CITY UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

Clustering analysis; Ensemble learning; Genetic guided clustering algorithms

Indexed keywords

GENETIC ALGORITHMS; LEARNING SYSTEMS; MATHEMATICAL OPERATORS;

ENSEMBLE LEARNING; FITNESS EVALUATIONS; GENETIC-GUIDED CLUSTERING ALGORITHMS; LEARNING OPERATORS;

CLUSTERING ALGORITHMS;

EID: 43249099468     PISSN: 01678655     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patrec.2008.02.017     Document Type: Article

References (27)

1. Demiriz, A., Bennett, K.P., Embrechts. M.J., 1999. Semi-supervised clustering using genetic algorithms. In: Proc. Artificial Neural Networks in Engineering.
2. Duda R.O., Hart P.E., and Stork D.G. Pattern classification. Pattern Classification (2001)
3. Du, J., Korkmaz, E., Alhajj, R., Barker, K., 2004. Novel clustering approach that employs genetic algorithm with new representation scheme and multiple objectives. In: Proc. Internat. Conf. on Data Warehousing and Knowledge Discovery.
4. Falkenauer E. A new representation and operators for genetic algorithms applied to grouping problems. Evolut. Comput. 2 (1994) 123-144
5. Fern, X.Z., Brodley, C.E., 2003. Clustering ensembles for high dimensional data clustering. In: Proc. Internat. Conf. on Machine Learning, pp. 186-193.
6. Fränti P. Genetic algorithm with deterministic crossover for vector quantization. Pattern Recognition Lett. 21 (2000) 61-68
7. Fred A., and Jain A.K. Combining multiple clusterings using evidence accumulation. IEEE Trans. Pattern Anal. Machine Intell. 27 (2005) 835-850
8. Garai G., and Chaudhuri B.B. A novel genetic algorithm for automatic clustering. Pattern Recognition Lett. 25 (2004) 173-187
9. Goldberg D.E. Genetic Algorithm in Search, Optimization and Machine Learning (1989), Addison-Wesley, Reading, MA
10. Ho T.K. The random subspace method for constructing decision forests. IEEE Trans. Pattern Anal. Machine Intell. 20 (1998) 832-844
11. Jain A.K., Murty M.N., and Flynn P.J. Data clustering: A review. ACM Comput. Sur. 13 (1999) 264-323
12. Jones, D.R., Beltramo, M.A., 1991. Solving partitioning problems with genetic algorithm. In: Proc. Internat. Conf. on Genetic Algorithm, pp. 442-449.
13. Krishna K., and Murty M. Genetic K-means algorithm. IEEE Trans. System Man Cybernet - Part B 29 (1999) 433-439
14. Kuncheva L.I., and Bezdek J.C. Nearest prototype classification: Clustering, genetic algorithms or random search?. IEEE Trans. Systems Man Cybernet. - Part B 28 (1998) 160-164
15. Kuncheva, L.I., Hadjitodorov, S.T., 2004. Using diversity in cluster ensembles. In: Proc. System, Man and Cybernetics, pp. 1214-1219.
16. Lu Y., Li S., Fotouhi F., Deng Y., and Brown S.J. Incremental genetic Kmeans algorithm and its application in gene expression data analysis. BMC Bioinform. (2004)
17. Martnez-Otzeta J.M., Sierra B., Lazkano E., and Astigarraga A. Classifier hierarchy learning by means of genetic algorithms. Pattern Recognition Lett. 27 (2006) 1998-2004
18. Mitra S. An evolutionary rough partitive clustering. Pattern Recognition Lett. 25 (2004) 1439-1449
19. Painho, M., Fernando, B., 2000. Using genetic algorithms in clustering problems. In: Proc. Conf. on GeoComputation.
20. Rand W.M. Objective criteria for the evaluation of clustering methods. J. Amer. Statist. Assoc. 66 (1971) 846-850
21. Rogers, A., Prügel-Bennett, A., 1999. Modelling the dynamics of a steady-state genetic algorithm. In: Proc. Foundation of Genetic Algorithms, pp. 57-68.
22. Sheng, W., Tucher, A., Liu, X., 2004. Clustering with niching genetic Kmeans algorithm. In: Proc. Genetic and Evolutionary Computation Conf., pp. 162-173.
23. Skurichina M., and Duin R. Bagging, boosting and the random subspace method for linear classifier. Pattern Anal. Appl. 5 (2002) 121-135
24. Strehl A., and Ghosh J. Clustering ensembles - A knowledge reuse framework for combining multiple partitions. J. Machine Learning Res. 3 (1999) 583-617
25. Syswerda, G., 1991. A study of reproduction in generational and steady state genetic algorithms. In: Proc. Foundation of Genetic Algorithms, pp. 94-101.
26. Viswanath, P., Jayasurya, K., 2006. A fast and efficient ensemble clustering method. In: Proc. Internat. Conf. on Pattern Recognition.
27. Whitley, D., Kauth, J., 1988. GENITOR: A different genetic algorithm. In: Proc. Rochy Mourntain Conf. on Artificial Intelligence.