BUILDING AN EFFICIENT CLASSIFICATION MODEL: A COMPARISON OF LOGISTICS REGRESSION AND ARTIFICIAL NEURAL NETWORK

The statistical models are applied in the social sciences is to understand and explain various phenomena occurring in the world around us. In order to be scientifically valid, reasonable and actionable, the building of such models should be inherited from the theory. To accomplish this, there is a need for methodologies that can enable social scientists to utilise their domain knowledge effectively even in the absence of strong a priori hypotheses. To explain the phenomenon , complex datasets containing hundreds of variables are analyzed to build potential models. This paper is an attempt to present an efficient Classification model highlighting the findings of Data Mining i.e. ANN and Statistical techniques i.e. logistics regression on same data set .