Publication

Abstract : The data which contains more number of Independent features or variables is known as High dimensional Data and its dimensions are staggeringly huge. In this type of data number of variables are more than number of observations. Gene expression data, Image data are examples for high dimensional data. Several methods have been introduced to handle high dimensional data. Out of these several methods Rough set theory based data analysis is effective way of handling data with uncertainty and incompleteness. It identifies the key pattern hidden in the data in the form of Decision Rules. It interprets the data with both qualitative and quantitative. This paper emphasis to classify the huge volume of data by constructing decision rules based on Rough Sets