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Knowledge Acquisition of Interval Set-Valued Based on Granular Computing

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Abstract:

The technique of a new extension of fuzzy rough theory using partition of interval set-valued is proposed for granular computing during knowledge discovery in this paper. The natural intervals of attribute values in decision system to be transformed into multiple sub-interval of [0,1]are given by normalization. And some characteristics of interval set-valued of decision systems in fuzzy rough set theory are discussed. The correctness and effectiveness of the approach are shown in experiments. The approach presented in this paper can also be used as a data preprocessing step for other symbolic knowledge discovery or machine learning methods other than rough set theory.

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Periodical:

Applied Mechanics and Materials (Volumes 543-547)

Pages:

2017-2023

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.543-547.2017

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Online since:

March 2014

Authors:

Qing Guan*, Jian He Guan

Keywords:

Decision Systems, Feature, Fuzzy Rough Set, Interval Partition, Interval Set-Valued

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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