期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2015
卷号：3
期号：8
DOI：10.15680/IJIRCCE.2015. 0308007
出版社：S&S Publications
摘要：Rough Set theory has been conceived as a tool to conceptualize, organize and analyze various types ofdata, in particular, to deal with inexact, uncertain or vague knowledge in applications related to Artificial Intelligence.In the case of classification, this theory implicitly calculates reducts of the full set of attributes, eliminating those thatare redundant or meaningless. Such reducts may even serve as input to other classifiers other than Rough Sets. Thetypical high dimensionality of current databases precludes the use of greedy methods to find optimal or suboptimalreducts in the search space and requires the use of stochastic methods. Rough set theory, which has been usedsuccessfully in solving problems in pattern recognition, machine learning, and data mining, centers around the idea thata set of distinct objects may be approximated via a lower and upper bound. In order to obtain the benefits that roughsets can provide for data mining and related tasks, efficient computation of these approximations is vital.
关键词：Rough set; Artificial Intelligence; greedy method; data mining; and approximations.
