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Uncertainty measurement for a three heterogeneous information system and its application in feature selection

  • Mathematical methods in data science
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Abstract

An information system (IS) is an important model in rough set theory. In practice applications, we often encounter an IS with different structures of information values. A three heterogeneous information system (3HIS) means an IS whose information values contain three types of data (i.e., scaled types, ordered types and normal types). This paper studies uncertainty measurement for a 3HIS and its application in feature selection. A 3HIS is first put forward. Then, the fuzzy relation on the object set with respect to each subsystem is defined. Next, four measure tools are used to assess the uncertainty of a 3HIS according to the fuzzy information granules induced by the defined fuzzy relation. Combining with the proposed measures, an application for feature selection in a 3HIS is given, and the corresponding algorithms based on the uncertainty measures are presented. Finally, numerical experiments are carried out and effectiveness analysis from the statistics perspective is done as so to evaluate the performance of the presented algorithms. The experimental results indicate that the proposed algorithm is more effective than some existing algorithms. These results will contribute to understanding the essence of uncertainty in a 3HIS.

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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 (11971420), Key Laboratory of Software Engineering in Guangxi University for Nationalities (2021-18XJSY-03), Guangxi Science and Technology Program (2017AD23056), Natural Science Foundation of Guangxi (AD19245102, 2020GXNSFAA159155, 2018GXNSFDA294003) and Special Scientific Research Project of Young Innovative Talents in Guangxi (2019AC20052).

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Authors and Affiliations

  1. School of Artificial Intelligence, Guangxi University for Nationalities, Nanning, 530006, Guangxi, People’s Republic of China

    Gangqiang Zhang & Liangdong Qu

  2. School of Mathematics and Statistics, Yulin Normal University, Yulin, 537000, Guangxi, People’s Republic of China

    Yan Song

  3. School of Mathematics and Physics, Guangxi University for Nationalities, Nanning, 530006, Guangxi, People’s Republic of China

    Shimin Liao

  4. Key Laboratory of Complex System Optimization and Big Data Processing in Department of Guangxi Education, Yulin Normal University, Yulin, 537000, Guangxi, People’s Republic of China

    Zhaowen Li

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  1. Gangqiang Zhang
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  2. Yan Song
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  3. Shimin Liao
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  4. Liangdong Qu
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  5. Zhaowen Li
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Contributions

GQZ designs the overall structure of the paper and writes the paper; Y. Song designs the overall structure of the paper; SML collects the data; LDQ implements the proposed method; ZWL writes the paper and improves the language.

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Correspondence to Yan Song or Zhaowen Li.

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Zhang, G., Song, Y., Liao, S. et al. Uncertainty measurement for a three heterogeneous information system and its application in feature selection. Soft Comput 26, 1711–1725 (2022). https://doi.org/10.1007/s00500-021-06722-0

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