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Granular Computing Classification Algorithms Based on Distance Measures between Granules from the View of Set
Joint Authors
Liu, Chunhua
Liu, Hongbing
Wu, Chang-an
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-03-06
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
Granular computing classification algorithms are proposed based on distance measures between two granules from the view of set.
Firstly, granules are represented as the forms of hyperdiamond, hypersphere, hypercube, and hyperbox.
Secondly, the distance measure between two granules is defined from the view of set, and the union operator between two granules is formed to obtain the granule set including the granules with different granularity.
Thirdly the threshold of granularity determines the union between two granules and is used to form the granular computing classification algorithms based on distance measures (DGrC).
The benchmark datasets in UCI Machine Learning Repository are used to verify the performance of DGrC, and experimental results show that DGrC improved the testing accuracies.
American Psychological Association (APA)
Liu, Hongbing& Liu, Chunhua& Wu, Chang-an. 2014. Granular Computing Classification Algorithms Based on Distance Measures between Granules from the View of Set. Computational Intelligence and Neuroscience،Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-488744
Modern Language Association (MLA)
Liu, Hongbing…[et al.]. Granular Computing Classification Algorithms Based on Distance Measures between Granules from the View of Set. Computational Intelligence and Neuroscience No. 2014 (2014), pp.1-9.
https://search.emarefa.net/detail/BIM-488744
American Medical Association (AMA)
Liu, Hongbing& Liu, Chunhua& Wu, Chang-an. Granular Computing Classification Algorithms Based on Distance Measures between Granules from the View of Set. Computational Intelligence and Neuroscience. 2014. Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-488744
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-488744