Capturing Uncertainty in Associative Classification Model

Capturing Uncertainty in Associative Classification Model

This paper aims to propose a weighted linguistic associative classification model for uncertainty data analysis using rough membership function. Transformation of quantitative association rules into linguistic representation can be achieved in discretizing the numerical interval into rough interval...

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Bibliographic Details
Main Authors: Choo, Yun Huoy, Abu Bakar, Azuraliza, Draman @ Muda, Azah Kamilah
Format: Conference or Workshop Item
Language:English
Published: 2009
Subjects:
Q Science (General)
T Technology (General)
AS Academies and learned societies (General)
Online Access:http://eprints.utem.edu.my/id/eprint/144/
http://eprints.utem.edu.my/id/eprint/144/1/CapturingUncertaintyInWeightedACModel_DMO09_CYH.pdf

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