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IJMLC 2014 Vol.4(4): 328-332 ISSN: 2010-3700
DOI: 10.7763/IJMLC.2014.V4.432

Comparisons between Rough Set Based and Computational Applications in Data Mining

En-Bing Lin and Yu-Ru Syau

Abstract—Rough set theory and wavelet theory are totally different areas of research in mathematics. We briefly describe each theory and apply them respectively to the same problem as an example of application in data mining. Furthermore, we compare the results we obtained from these two different approaches of the same application. Future study along this line of research is also mentioned.

Index Terms—Information system, rough set theory, wavelet, denoising.

E. B. Lin is with Central Michigan University, Mt. Pleasant, MI, USA (e-mail: enbing.lin@cmich.edu).
Y. R. Syau is with National Formosa University, Yunlin, Taiwan (e-mail: yrsyau@nfu.edu.tw).


Cite: En-Bing Lin and Yu-Ru Syau, "Comparisons between Rough Set Based and Computational Applications in Data Mining," International Journal of Machine Learning and Computing vol.4, no. 4, pp. 328-332, 2014.

General Information

  • ISSN: 2010-3700 (Online)
  • Abbreviated Title: Int. J. Mach. Learn. Comput.
  • Frequency: Bimonthly
  • DOI: 10.18178/IJMLC
  • Editor-in-Chief: Dr. Lin Huang
  • Executive Editor:  Ms. Cherry L. Chen
  • Abstracing/Indexing: Inspec (IET), Google Scholar, Crossref, ProQuest, Electronic Journals Library.
  • E-mail: ijmlc@ejournal.net

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