An Empirical comparison of rule based classification techniques in medical databases

Classification techniques have been widely applied in the field of medical databases and have gained a lot of success. At present various classification algorithms are available in the literature and the problem of choosing the best method for a particular data set is faced by many researchers. In this paper, we apply five well-known rule based classification techniques, Decision Tree, JRIP, NNGE, PART and RIDOR, on different medical databases and compare their relative merits & demerits. Subsequently, we interpret their applicability to segment patients into groups.