An Approach of Rough Set for Data Fusion

Rough Set Approach for Categorical Data Clustering

A few techniques of rough categorical data clustering exist to group objects having similar characteristics. However, the performance of the techniques is an issue due to low accuracy, high computational complexity and clusters purity. This work proposes a new technique called Maximum Dependency Attributes (MDA) to improve the previous techniques due to these issues. The proposed technique is b...

Mining Incomplete Data - A Rough Set Approach

Mining Numerical Data - A Rough Set Approach

Rough set approach to incomplete numerical data

The theory rough set successfully implemented diberbagai sector , but rough set model classical can only associated with the data complete and set of data in symbolic form ( Jianhua , dai , 2013 ) . Research by adopting the theory rough set conducted in attribute numerical and the value of an attribute lost ( Jerzy w , Grzymala-Buse and Zdzislaw S , Hippe , Nov .2011 ) .In this research discuss...

Application of Rough Set Theory in Data Mining for Decision Support Systems (DSSs)

Decision support systems (DSSs) are prevalent information systems for decision making in many competitive business environments. In a DSS, decision making process is intimately related to some factors which determine the quality of information systems and their related products. Traditional approaches to data analysis usually cannot be implemented in sophisticated Companies, where managers ne...