Attribute Reduction Approaches Based on Rough Set Theory: A Analytical Review |
Author(s): |
| Jatin Bedi , Department of Computer Science &Application,K.U.K; Dr. shuchita Upadhyaya, Department of Computer Science &Application,K.U.K |
Keywords: |
| Attribute Reduction, Feature Selection, Rough Set Theory, Reduct |
Abstract |
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Feature selection aims to determine a minimal attribute subset while preserving a suitably high accuracy in representing the original features. Rough set theory is an approach to deal with uncertainty and vagueness. It has been successfully applied to various fields. An important concept of rough set theory is an attribute reduct i.e. a subset of attributes that can fully characterize the knowledge in the database and are necessary for preserving the particular property of information table. Several researchers have provided the various algorithms for computing the reduct set (feature selection) for information table. This paper focuses on fundamental ideas behind Rough Set Theory based approaches and reviews related feature selection methods based on these ideas. |
Other Details |
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Paper ID: IJSRDV3I30294 Published in: Volume : 3, Issue : 3 Publication Date: 01/06/2015 Page(s): 524-526 |
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