A new discrete particle swarm algorithm applied to attribute selection in a bioinformatics data set

GECCO 2006 - Genetic and Evolutionary Computation Conference

Volumn 1, Issue , 2006, Pages 35-42

  Correa, Elon S ^a   Freitas, Alex A ^a   Johnson, Colin G ^a  

^a UNIVERSITY OF KENT   (United Kingdom)

Author keywords

Attribute selection; Bioinformatics; Data Mining; Naive Bayes classifier; Optimization; Particle swarm

Indexed keywords

DATABASE SYSTEMS; EVOLUTIONARY ALGORITHMS; MATHEMATICAL MODELS;

ATTRIBUTE SELECTION; BIOINFORMATICS; NAIVE BAYES CLASSIFIER; PARTICLE SWARM OPTIMIZATION (PSO) ALGORITHM;

DATA MINING;

EID: 33750269682     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1143997.1144003     Document Type: Conference Paper

References (18)

1. T. Blackwell and J. Branke. Multi-swarm optimization in dynamic environments. In Lecture Notes in Computer Science, volume 3005, pages 489-500. Springer-Verlag, 2004.
2. E. S. Correa, M. T. Steiner, A. A. Freitas, and C. Carnieri. Using a genetic algorithm for solving a capacity p-median problem. Numerical Algorithms, 35:373-388, 2004.
3. D. Freedman, R: Pisani, and R. Purves. Statistics. W. W. Norton & Company, 3rd edition, September 1997.
4. A. A. Freitas. Data Mining and Knowledge Discovery with Evolutionary Algorithms. Springer-Verlag, October 2002.
5. S. Janson and M. Middendorf. A hierarchical particle swarm optimizer for dynamic optimization problems. In Evoworkshops 2004: 1st European Workshop on Evolutionary Algorithms in Stochastic and Dynamic Environments, pages 513-524, Coimbra, Portugal, 2004. Springer-Verlag.
6. G. Kendall and Y. Su. A particle swarm optimisation approach in the construction of optimal risky portfolios. In Proceedings of the 23rd IASTED International Multi-Conference on Applied Informatics, pages 140-145, 2005. Artificial intelligence and applications.
7. J. Kennedy.; Small worlds and mega-minds: effects of neighborhood topology on particle swarm performance. In P. J. Angeline, Z. Michalewicz, M. Schoenauer, X. Yao, and A. Zalzala, editors, Proceedings of the Congress of Evolutionary Computation, pages 1931-1938, Piscataway, NJ, USA, 1999. IEEE Press.
8. J. Kennedy and R. C. Eberhart. A discrete binary Aversion of the particle swarm algorithm. In Proceedings of the 1997 Conference on Systems, Man, and Cybernetics, pages 4104-4109, Piscataway, NJ, USA, 1997. IEEE.
9. J. Kennedy and R. C. Eberhart. Swarm Intelligence. Morgan Kaufmann Publishers Inc., San Francisco, CA, USA, 2001.
10. M. Løvbjerg and T. Krink. Extending particle swarm optimisers with self-organized criticality. In D. B. Fogel, M. A. El-Sharkawi, X. Yao, G. Greenwood, H. Iba, P. Marrow, and M. Shackleton, editors, Proceedings of the 2002 Congress on Evolutionary Computation CEC2002; pages 1588-1593. IEEE Press, 2002.
11. T. M. Mitchell. Machine Learning. McGraw-Hill, August 1997.
12. A. Papoulis and S. U. Pillai. Probability, Random Variables and Stochastic Processes With Errata Sheet. McGraw-Hill, 1st edition, December 2001.
13. G. L. Pappa, A. J. Baines, and A. A. Freitas. Predicting post-synaptic activity in proteins with data mining. Bioinformatics, 21(2):ii19-ii25, 2005.
14. R. Poli, C. D. Ohio, and W. B. Langdon. Exploring extended particle swarms: a genetic programming approach. In GECCO'05: Proceedings of the 2005 Conference on Genetic and Evolutionary Computation, pages 169-176, New York, NY, USA, 2005. ACM Press.
15. R. Rapport. Nerve Endings: the Discovery of the Synapse. W. W. Norton & Company, May 2005.
16. Y. Shi and R. C. Eberhart. Parameter selection in particle swarm optimization. In EP'98: Proceedings of the 7th International Conference on Evolutionary Programming, pages 591-600, London, UK, 1998. Springer-Verlag.
17. M. M. Solomon. Algorithms for the vehicle routing and scheduling problems with time window constraints. Operations Research, 35(2):254-265, 1987.
18. I. H. Witten and E. Frank. Data Mining: Practical Machine Learning Tools and Techniques. Morgan Kaufmann, 2nd edition, 2005.