Vol. 6 (04) pp. 128-131 DOI: 10.21474/IJAR01/6834

A STUDY OF DM TECHNIQUES IN SOFT COMPUTING FRAMEWORK.

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  • Research Scholar, Department of Electronics and Computer Science, RTM Nagpur University, Nagpur.
  • Asso. Prof. and Head Department of Computer Science,S.S.E.S Science College,, Nagpur.
  • Prof. and Head, Department of Electronics and Computer Science, RTM Nagpur University, Nagpur.
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Abstract

Data Mining is one of the fundamental steps in KDD process and is concerned with the algorithmic means by which patterns or structures are enumerated from the data under acceptable computational efficiency. Soft computing tools are individually or in integrated manner, are turning out to be strong candidates for performing Data mining Tasks efficiently. The main constitutes of soft computing indicates Fuzzy logic, Neural networks, Genetic Algorithms and Rough sets. Each of them contributes a distinct methodology for addressing problems in its domain. This is done in a co-operative, rather than a competitive manner. The result is a more intelligent and robust system providing a human ? interpretable, low cost, approximate solution, as compared to traditional techniques.The present article provides an overview of the available literature on use of data mining in the soft computing framework.

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References

  1. B. Tickle, R. Andrews, M. Golea, and J. Diederich, ?The truth will come to light: Directions and challenges in extracting the knowledge embedded within trained artificial neural networks,? IEEE Trans. Neural Networks, vol. 9, pp. 1057?1068, 1998.
  2. M. Fayyad, G. Piatetsky-Shapiro, P. Smyth, and R. Uthurusamy, Eds., Advances in Knowledge Discovery and Data Mining. Menlo Park, CA:AAAI/MIT Press, 1996.
  3. ?Special issue on knowledge discovery in data- and knowledge bases,? Int. J. Intell. Syst., vol. 7, 1992.
  4. A. Zadeh, ?Fuzzy logic, neural networks, and soft computing,? Commun. ACM, vol. 37, pp. 77?84, 1994.
  5. K. Pal and S. Mitra, Neuro-Fuzzy Pattern Recognition: Methods in Soft Computing. New York: Wiley, 1999.
  6. E. Goldberg, Genetic Algorithms in Search, Optimization, and Machine Learning, Addison-Wesley, 1989.
  7. Dataminig Concepts and Techniques- Jiawei Han, MichelineKamber.
  8. Effective Data Mining Using Neural Networks Hongjun Lu, Rudy Setiono, and Huan Liu, IEEE Transactions on knowledge and data engineering, vol. 8, No. 6 December 1996.
  9. Mitra and S. K. Pal, ?Fuzzy multi-layer perceptron, inferencing and rule generation,? IEEE Trans. Neural Networks, vol. 6, pp. 51?63, 1995.
  10. F. Baldwin, ?Knowledge from data using fuzzy methods,? Pattern Recognition Lett., vol. 17, pp. 593?600, 1996.
  11. Principles of Soft Computing-S. N. Sivanandam and S. N. Deepa.
  12. Grzymala-Busse, R.Swiniarski, N. Zhong and Z. Zizrko International Journel of Apploied mathematics and Computer science, Special Issue on Rough Sets, and Its Applications.
  13. Pawlak, Rough Sets, Theoretical Aspects of Reasoning about Data. Dordrecht: Kluwer, 1991. A. Skowron and C. Rauszer, ?The Discernibility Matrices and functions in Information Systems,? Intelligent Decision Support, Handbook of Applications and Advances of the Rough Sets Theory, R. Slowi_nski, ed. pp. 331- 362, Dordrecht: Kluwer Academic, 1992.
  14. Wei and G. Chen, ?Mining generalized association rules with fuzzy taxonomic structures,? in Proc. NAFIPS 99, New York, June 1999, pp. 477?481.
  15. W. Flockhart and N. J. Radcliffe, ?A genetic algorithm-based approach to data mining,? in Proc. 2nd
  16. Conf. Knowledge Discovery DataMining (KDD-96). Portland, OR, Aug. 2?4, 1996, p. 299.
  17. L. Raymer, W. F. Punch, E. D. Goodman, and L. A. Kuhn, ?Genetic programming for improved data mining: An application to the biochemistry of protein interactions,? in Proc. 1st Annu. Conf. Genetic Programming 1996, Stanford Univ., CA, July 28?31, 1996, pp. 375?380.
  18. Mitra and Y. Hayashi, ?Neuro-fuzzy rule generation: Survey in soft computing framework,? IEEE Trans. Neural Networks, vol. 11, pp. 748?768, 2000

How to Cite This Article

R. K. Dhuware, S.R. Pande and S. J. Sharma. (2018); A STUDY OF DM TECHNIQUES IN SOFT COMPUTING FRAMEWORK., Int. J. of Adv. Res., 6 (04), 128-131, ISSN 2320-5407. DOI: https://doi.org/10.21474/IJAR01/6834

Corresponding Author

Prof. R. K. Dhuware

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