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Journal of Classification
Published in: Journal of Classification 1/2021

18-02-2020

Spherical Classification of Data, a New Rule-Based Learning Method

Authors: Zhengyu Ma, Hong Seo Ryoo

Published in: Journal of Classification | Issue 1/2021

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Abstract

This paper presents a new rule-based classification method that partitions data under analysis into spherical patterns. The forte of the method is twofold. One, it exploits the efficiency of distance metric-based clustering to fast collect similar data into spherical patterns. The other, spherical patterns are each a trait shared among one type of data only, hence are built for classification of new data. Numerical studies with public machine learning datasets from Lichman (2013), in comparison with well-established classification methods from Boros et al. (IEEE Transactions on Knowledge and Data Engineering, 12, 292–306, 2000) and Waikato Environment for Knowledge Analysis (http://​www.​cs.​waikato.​ac.​nz/​ml/​weka/​), demonstrate the aforementioned utilities of the new method well.
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Metadata
Title
Spherical Classification of Data, a New Rule-Based Learning Method
Authors
Zhengyu Ma
Hong Seo Ryoo
Publication date
18-02-2020
Publisher
Springer US
Published in
Journal of Classification / Issue 1/2021
Print ISSN: 0176-4268
Electronic ISSN: 1432-1343
DOI
https://doi.org/10.1007/s00357-019-09355-z

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