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: email@example.com).
Y. R. Syau is with National Formosa University, Yunlin, Taiwan (e-mail: firstname.lastname@example.org).
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.