期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2013
卷号：4
期号：10
DOI：10.14569/IJACSA.2013.041019
出版社：Science and Information Society (SAI)
摘要：Because of the patient’s inconsistent data, uncertain Thyroid Disease dataset is appeared in the learning process: irrelevant, redundant, missing, and huge features. In this paper, Rough sets theory is used in data discretization for continuous attribute values, data reduction and rule induction. Also, Rough sets try to cluster the Thyroid relation attributes in the presence of missing attribute values and build the Modified Similarity Relation that is dependent on the number of missing values with respect to the number of the whole defined attributes for each rule. The discernibility matrix has been constructed to compute the minimal sets of reducts, which is used to extract the minimal sets of decision rules that describe similarity relations among rules. Thus, the rule associated strength is measured.
