Attribute Reduction Based on Rough Neighborhood Approximation

One of the main obstacles facing current data mining techniques is attribute reduction. This paper discusses the basic concepts of rough set, and studies two rough approximations operators under neighborhood systems. An attribute reduction method based on rough set theory and neighborhood systems is...

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Bibliographic Details
Main Authors: Ming He, Yong-ping Du
Format: Conference Proceeding
Language:English
Subjects:
approximation
Artificial intelligence
attribute reduction
Computer science
Computer science education
Data mining
Educational technology
Helium
Information systems
neighborhood systems
Pattern recognition
rough set theory
Rough sets
Set theory
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Summary:One of the main obstacles facing current data mining techniques is attribute reduction. This paper discusses the basic concepts of rough set, and studies two rough approximations operators under neighborhood systems. An attribute reduction method based on rough set theory and neighborhood systems is presented. The experimental results show that the method of attributes reduction with rough sets and neighborhood system is feasible and valid.
DOI:10.1109/ETCS.2009.85