Quotation Leung, Yee, Fischer, Manfred M., Wu, Wei-Zhi, Mi, Ju-Sheng. 2008. A rough set approach for the discovery of classification rules in interval-valued information systems. International Journal of Approximate Reasoning 47 (2), 233-246.


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Abstract

A novel rough set approach is proposed in this paper to discover classification rules through a process of knowledge induction which selects decision rules with a minimal set of features for classification of real-valued data. A rough set knowledge discovery framework is formulated for the analysis of interval-valued information systems converted from real-valued raw decision tables. The minimal feature selection method for information systems with interval-valued features obtains all classification rules hidden in a system through a knowledge induction process. Numerical examples are employed to substantiate the conceptual arguments.

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Publication's profile

Status of publication Published
Affiliation WU
Type of publication Journal article
Journal International Journal of Approximate Reasoning
Citation Index SCI
Language English
Title A rough set approach for the discovery of classification rules in interval-valued information systems
Volume 47
Number 2
Year 2008
Page from 233
Page to 246
Reviewed? Y
DOI 10.1016/j.ijar.2007.05.001

Associations

People
Fischer, Manfred M. (Details)
External
Leung, Yee (Chinese University of Hongkong, China)
Mi, Ju-Sheng (College of Mathematics and Information Science, Hebei Normal University, China)
Wu, Wei-Zhi (Information College, Zhejiang Ocean University, China)
Organization
Research Institute for Supply Chain Management FI (Details)
Institute for Economic Geography and GIScience IN (Details)
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