A Rough Sets Based Classifier for Primary Biliary Cirrhosis

In this paper, a decision support system is presented based on the machine learning approach of rough sets. The resulting decision support system was able to reduce the dimensionality of the data, produce a highly accurate classifier, and generate a rule based classifier that is readily understood by a domain expert. These preliminary results indicate that the rough sets machine learning approach can be successfully applied to biomedical datasets that contain a variety of attribute types, missing values and multiple decision classes