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Measures of uncertainty for a four-hybrid information system and their applications

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Abstract

A four-hybrid information system (4HIS) is an information system where the dataset of object descriptions consists of categorical, boolean, real-valued and missing data or attributes. This paper studies measures of uncertainty for a 4HIS and its application in attribute reduction. The distance function for each type of attribute in a 4HIS is first provided. Then, this distance is used to produce the tolerance relation induced by a given subsystem in a 4HIS. Next, information structure of this subsystem is proposed in terms of a set vector and dependence between information structures is introduced. Moreover, granulation and entropy measures in a 4HIS are investigated on the basis of information structures. In order to verify the feasibility of the proposed measures, effectiveness analysis is performed from a statistical perspective. Finally, an application of the proposed measures for attribute reduction in a 4HIS is given.

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Acknowledgements

The authors would like to thank the editors and the anonymous reviewers for their valuable comments and suggestions, which have helped immensely in improving the quality of the paper. This work is supported by National Natural Science Foundation of China (11761012, 11861010), National Natural Science Foundation of Guangxi Province (2018GXNSFFA281008) and Cultivation Plan of Thousands of Young Backbone Teachers in Higher Education Institutions of Guangxi Province.

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Authors and Affiliations

  1. School of Information and Statistics, Guangxi University of Finance and Economics, Nanning, 530003, Guangxi, People’s Republic of China

    Bin Qin, Fanping Zeng & Kesong Yan

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  1. Bin Qin
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  2. Fanping Zeng
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  3. Kesong Yan
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Correspondence to Bin Qin.

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Qin, B., Zeng, F. & Yan, K. Measures of uncertainty for a four-hybrid information system and their applications. Soft Comput 26, 3643–3662 (2022). https://doi.org/10.1007/s00500-022-06827-0

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