Abstract

Data mining has as goal to extract knowledge from large databases. To extract this knowledge, a database may be considered as a large search space, and a mining algorithm as a search strategy. In general, a search space consists of an enormous number of elements, making an exhaustive search infeasible. Therefore, efficient search strategies are of vital importance. Search strategies based on genetic-based algorithms have been applied successfully in a wide range of applications. In this paper, we discuss the suitability of genetic-based algorithms for data mining. We discuss the various application areas where genetic Algorithm plays evolutionary role with data mining technique and explain them in details.

References

• Forrest, Stephanie. "Genetic algorithms: principles of natural selection applied to computation. " Science, vol. 261, p. 872-878 (1993).
• Bandyopadhyay, S. , and Muthy, C. A. "Pattern Classification Using Genetic Algorithms".
• Jain, A. K. ; Zongker, D. "Feature Selection: Evaluation, Application, and Small Sample Performance", IEEE Transaction on Pattern Analysis and Machine Intelligence, Vol. 19, No. 2, February (1997).
• Pattern Recognition Letters, (1995). Vol. 16, pp. 801-808.
• Erick Cantu-Paz, "Feature Subset Selection, Class Separability, and Genetic Algorithms", Center for Applied Scientic Computing Lawrence Livermore National Laboratory Livermore, CA, (1994).
• Siedlecki, W. , Sklansky J. , A note on genetic algorithms for large-scale feature selection, Pattern Recognition Letters, Vol. 10, Page 335-347, (1989).
• Agrawal, R. , and R. Srikant. 1994. Fast algorithms for mining association rules. In Proceedings of the 20th international conference on very large databases held in Santiago, Chile, September 12-15, 1994, 487-99. San Francisco, CA: Morgan Kaufmann.
• M. M itchell (1997) an introduction to genetic Algorithm MIT press MA.
• Agrawal, R. , and R. Srikant. 1994. Fast algorithms for mining association rules. In Proceedings of the 20th international conference on very large databases held in Santiago, Chile, September 12-15, 1994, 487-99. San Francisco, CA: Morgan Kaufmann.
• Pei, M. , Punch, W. F. , and Goodman, E. D. "Feature Extraction Using Genetic Algorithms", Proceeding of International Symposium on Intelligent Data Engineering and Learning'98 (IDEAL'98), Hong Kong, Oct. (1998).
• Wright, A. W. "Genetic Algorithms for real-parameter optimization", In Rawlings, R. E. (ed) Foundations of Genetic Algorithms, 1990, pp 205 -220, Morgan Kaufman.
• Chen, S. H. Genetic Algorithms and Genetic Programming in Computational Finance. Boston, MA: Kluwer. 2002.