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A New Multi-classifier Ensemble Algorithm Based on D-S Evidence Theory

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Abstract

Classifier ensemble is an important research content of ensemble learning, which combines several base classifiers to achieve better performance. However, the ensemble strategy always brings difficulties to integrate multiple classifiers. To address this issue, this paper proposes a multi-classifier ensemble algorithm based on D-S evidence theory. The principle of the proposed algorithm adheres to two primary aspects. (a) Four probability classifiers are developed to provide redundant and complementary decision information, which is regarded as independent evidence. (b) The distinguishing fusion strategy based on D-S evidence theory is proposed to combine the evidence of multiple classifiers to avoid the mis-classification caused by conflicting evidence. The performance of the proposed algorithm has been tested on eight different public datasets, and the results show higher performance than other methods.

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Acknowledgements

This research was funded by Application of collaborative precision positioning service for mass users (2016YFB0501805-1), National Development and Reform Commission integrated data service system infrastructure platform construction project (JZNYYY001), Guangxi Key Lab of Multi-source Information Mining & Security (MIMS21-M-04).

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Authors and Affiliations

  1. College of Information and Electrical Engineering, China Agricultural University, Beijing, 100083, China

    Kaiyi Zhao, Zeqiu Chen, Ruizhi Sun, Gang Yuan & Jiayao Li

  2. Guangxi Key Lab of Multi-source Information Mining & Security, Guangxi Normal University, Guilin, 541004, China

    Li Li

  3. Computer School, Beijing Information Science and Technology University, Beijing, 100101, China

    Li Li

  4. Scientific Research Base for Integrated Technologies of Precision Agriculture (Animal Husbandry), The Ministry of Agriculture, Beijing, 100083, China

    Ruizhi Sun

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  1. Kaiyi Zhao
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  2. Li Li
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Correspondence to Ruizhi Sun or Gang Yuan.

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Zhao, K., Li, L., Chen, Z. et al. A New Multi-classifier Ensemble Algorithm Based on D-S Evidence Theory. Neural Process Lett 54, 5005–5021 (2022). https://doi.org/10.1007/s11063-022-10845-2

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