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Rough Set is a valid mathematical theory developed in recent years, which has been applied successfully in such fields as machine learning, data mining, intelligent data analyzing and control algorithm acquiring. In this paper, the authors discuss the reduction of knowledge using conditional entropy in rough set theory. First, the changing tendency of the conditional entropy of decision attributes giving condition attributes is studied from the viewpoint of information. Next, a new reduction algorithm based on conditional entropy is developed. Furthermore, our simulation results show that the algorithm can find the minimal reduction in most cases.
Rough Set is a valid mathematical theory developed in recent years, which has been applied successfully in such fields as machine learning, data mining, intelligent data analyzing and control algorithm acquiring. In this paper, the authors discuss the reduction of knowledge using conditional entropy in rough set theory. First, the changing tendency of the conditional entropy of decision attributes giving condition attributes is studied from the viewpoint of information. Next, a new reduction algorithm based on conditional entropy is developed. Furthermore, our simulation results show that the algorithm can find the minimal reduction in most cases.