Rough Neural Network

Data mining is used for reducing the high dimensional data into extensively simpler variables without affecting the quality of data. This paper demonstrates different techniques used in data mining based on Rough sets. The main objective of Rough set theory discovers high dimensional data base from hidden patters of data without expecting additional parameter. Rough Hybridization with Fuzzy Sets, Neural Networks, Genetic and Evolutionary algorithm will be very effective in data mining and they resulted in classifiers of better quality. This paper describes the advantages of Rough hybridization with neural network, which is implemented in the high dimensional database.