Classification Rule Generation for Diabetic Patients using Rough Set Approach - Ghosh, Kasturi; Mukhopadhyay, Sripati (International Journal of Computer Sciences and Engineering, 2015)
Classification rule-generation is a Data Mining activity. A supervised process uses a training data set to generate the rules. The objective is to predict a predefined class or goal attribute, which can never appear in the antecedent part of a rule. The generated rules are used to predict the class attribute of an unknown test data set. In this paper we have tried to generate classification rule for diabetic patients using Rough set. This present research work relates Data mining to Health Informatics. The proposed algorithm generates the different classification rules related to predict insulin dose depending upon blood glucose measurement and helps in diabetes monitoring.