DOI: 10.5176/2251-1911_CMCGS16.9
Authors: Dr.K.Anitha
Abstract: Data Clustering is the process of dividing a data set into groups of similar items. This paper describes the data analysis technique based on Rough sets. The main objective of data analysis using Rough Set theory is it discovers hidden patterns of data from high dimensional data base. Moreover Rough set data analysis is very effective when it combines with other intelligent tools like Fuzzy, Genetic Algorithm and Neural Network, this process is known as hybridization. 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 exhibits comparative analysis of classification results performed by Rough sets with their hybridization technique for biological data mining
Keywords: Rough Sets, Fuzzy-Rough Sets, Rough Set Attribute Reduction, Fuzzy Lower and Upper Approximation.
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