Paper Title
Information Gain With Regression For Differentiation of Cognitive Impairments

Abstract
Cognitive Impairment (CI) is a general term that describes specific kinds of problems. The differentiation of Cognitive Impairment is a very complicated task. It is very difficult to the identification of CI from diverse features or signs. There are different types of cognitive impairments and they are life-long. The main aim of this paper is to develop a hybridized classifier model and determine its relevance in CI differentiation for helping in medical diagnosis. In achieving this aim, a hybridized classifier using regression with information gain is developed and its performance is evaluated. The results of the study show that the developed hybridized classifier has very good contribution in prediction system and capable of improving the performance of classifiers. Keywords— Regression, Data Mining, Information Gain, Cognitive Impairment.