Towards the use of metaheuristics for optimizing the combination of classifier and cluster ensembles

Proceedings - 1st BRICS Countries Congress on Computational Intelligence, BRICS-CCI 2013

Volumn , Issue , 2013, Pages 483-488

  Coletta, Luiz F S ^a   Hruschka, Eduardo R ^a   Acharya, Ayan ^b   Ghosh, Joydeep ^b  

^a UNIVERSITY OF SÃO PAULO   (Brazil)

^b The University of Texas at Austin   (United States)

Author keywords

Classification; Clustering; Ensembles; Metaheuristics

Indexed keywords

ARTIFICIAL INTELLIGENCE; CLASSIFICATION (OF INFORMATION); HEURISTIC ALGORITHMS; PARAMETER ESTIMATION;

CLUSTERING; COMBINATION OF CLASSIFIERS; COMBINING CLASSIFIERS; COMPUTATIONALLY EFFICIENT; ENSEMBLES; GENERAL OPTIMIZATIONS; META HEURISTICS; STATISTICAL SIGNIFICANCE;

CLUSTERING ALGORITHMS;

EID: 84905380262     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/BRICS-CCI-CBIC.2013.86     Document Type: Conference Paper

References (35)

1. L. I. Kuncheva, Combining Pattern Classifiers: Methods and Algorithms. Hoboken, NJ: Wiley-Interscience, 2004
2. J. Kittler and F. Roli, Eds., Multiple Classifier Systems. LNCS Vol. 2634, Springer, 2002
3. K. Tumer and J. Ghosh, "Analysis of decision boundaries in linearly combined neural classifiers," Pattern Recognition, vol. 29, no. 2, pp. 341-348, 1996
4. N. C. Oza and K. Tumer, "Classifier ensembles: Select real-world applications," Information Fusion, vol. 9, no. 1, pp. 4-20, 2008
5. J. Ghosh and A. Acharya, "Cluster ensembles," Wiley Interdisc. Rew.: Data Mining and Knowledge Discovery, vol. 1, no. 4, pp. 305-315, 2011
6. S. Basu, I. Davidson, and K. Wagstaff, Constrained Clustering: Advances in Algorithms, Theory, and Applications, 1st ed. Chapman &Hall/CRC Press, 2008
7. A. Acharya, E. R. Hruschka, J. Ghosh, and S. Acharyya, "C3E: A framework for combining ensembles of classifiers and clusterers," in Multiple Classifier Systems. LNCS Vol. 6713, Springer, 2011, pp. 269-278
8. I. Rechenberg, Evolutionsstrategie: Optimierung Technischer Systeme nach Prinzipien Der Biologischen Evolution, ser. Problemata. Stuttgart-Bad Cannstatt: Frommann-Holzboog Verlag, 1973, no. 15
9. H. P. Schwefel, Numerical Optimization of Computer Models. Chichester: John Wiley &Sons, Inc., 1981
10. K. Price, "Differential evolution: A fast and simple numerical optimizer,"in Fuzzy Information Processing Society, 1996. NAFIPS. 1996 Biennial Conference of the North American. IEEE, 1996, pp. 524-527
11. N. Hansen and A. Ostermeier, "Completely derandomized selfadaptation in evolution strategies," Evol. Comput., vol. 9, no. 2, pp. 159-195, 2001
12. S. Kirkpatrick, C. D. Gelatt, and M. P. Vecchi, "Optimization by Simulated Annealing," Science, Number 4598, vol. 220, 4598, pp. 671-680, 1983
13. J. Kennedy and R. Eberhart, "Particle swarm optimization," in Neural Networks, 1995. Proceedings., IEEE International Conference on, vol. 4, 1995, pp. 1942-1948
14. A. Strehl and J. Ghosh, "Cluster Ensembles-A Knowledge Reuse Framework for Combining Multiple Partitions," Journal of Machine Learning Research, vol. 3, pp. 583-617, 2002
15. A. Banerjee, S. Merugu, I. S. Dhillon, and J. Ghosh, "Clustering with bregman Divergences," J. Mach. Learn. Res., vol. 6, pp. 1705-1749, 2005
16. S. Boyd, N. Parikh, E. Chu, B. Peleato, and J. Eckstein, "Distributed optimization and statistical learning via the alternating direction method of multipliers," Found. Trends Mach. Learn., vol. 3, no. 1, pp. 1-122, 2011
17. T. Bäck, F. Hoffmeister, and H. P. Schwefel, "A survey of evolution strategies," in Proceedings of the Fourth International Conference on Genetic Algorithms, 1991, pp. 2-9
18. T. Bäck and H.-P. Schwefel, "An overview of evolutionary algorithms for parameter optimization," Evol. Comput., vol. 1, pp. 1-23, 1993
19. X.-S. Yang, Nature-Inspired Metaheuristic Algorithms, 2nd ed. Luniver Press, 2010
20. A. E. Eiben and J. E. Smith, Introduction to Evolutionary Computing (Natural Computing Series). Springer, 2008
21. T. Bäck, D. B. Fogel, and Z. Michalewicz, Handbook of Evolutionary Computation, 1st ed. Bristol, UK: IOP Publishing, 1997
22. A. A. Freitas, A survey of evolutionary algorithms for data mining and knowledge discovery. New York, USA: Springer-Verlag Inc., 2003, pp. 819-845
23. N. Hansen, "The CMA evolution strategy: A comparing review," in Towards a New Evolutionary Computation, ser. Studies in Fuzziness and Soft Computing. Springer Berlin / Heidelberg, 2006, vol. 192, pp. 75-102
24. R. Storn and K. Price, "Differential evolution-A simple and efficient heuristic for global optimization over continuous spaces," Jornal of Global Optimization, vol. 11, no. 4, pp. 341-359, 1997
25. J. Vesterstrom and R. Thomsen, "A comparative study of differential evolution, particle swarm optimization, and evolutionary algorithms on numerical benchmark problems," in Evolutionary Computation. CEC2004. Congress on, vol. 2, 2004, pp. 1980-1987 Vol.2
26. P. J. M. Laarhoven and E. H. L. Aarts, Eds., Simulated annealing: Theory and applications. Norwell, MA, USA: Kluwer Academic Publishers, 1987
27. Eberhart and Y. Shi, "Particle swarm optimization: Developments, applications and resources," in Evolutionary Computation, 2001. Proceedings of the 2001 Congress on, vol. 1, 2001, pp. 81-86 vol. 1
28. Y. Shi and R. C. Eberhart, "Parameter selection in particle swarm optimization," in Proceedings of the 7th International Conference on Evolutionary Programming VII, ser. EP ?98. London, UK: Springer-Verlag, 1998, pp. 591-600
29. I. H. Witten and E. Frank, Data mining: Practical machine learning tools and techniques, 2nd ed., ser. Morgan Kaufmann Series in Data Management Systems. Morgan Kaufmann, 2005
30. J. Bergstra and Y. Bengio, "Random search for hyper-parameter optimization,"J. Mach. Learn. Res., vol. 13, pp. 281-305, 2012
31. A. Frank and A. Asuncion, "UCI Machine Learning Repository [http://archive.ics.uci.edu/ml]," University of California, Irvine, School of Information and Computer Sciences. 2010
32. A. K. Jain, "Data clustering: 50 years beyond k-means," Pattern Recognition Letters, vol. 31, no. 8, pp. 651-666, 2010
33. R. Campello and E. Hruschka, "A fuzzy extension of the silhouette width criterion for cluster analysis," Fuzzy Sets and Systems, vol. 157, no. 21, pp. 2858-2875, 2006
34. E. R. Hruschka, R. J. Campello, and L. N. D. Castro, "Evolving clusters in gene-expression Data," Information Sciences, vol. 176, no. 13, pp. 1898-1927, 2006
35. J. Demšar, "Statistical comparisons of classifiers over multiple data sets," J. Mach. Learn. Res., vol. 7, pp. 1-30, 2006.