Abstract
Evidential clustering, based on the notion of credal partition, has been successfully applied in many fields, reflecting its broad appeal and usefulness as one of the steps in exploratory data analysis. However, it is time-consuming due to the introduction of meta-cluster, which is regarded as a new cluster and defined by the disjunction (union) of several special (singleton) clusters. In this paper, a simple and fast method is proposed to extract the credal partition structure in evidential clustering based on modifying the iteration rule. By doing so, the invalid computation associated with meta-clusters is effectively eliminated. It is superior to known methods in terms of execution time. The results show the potential of the proposed method, especially in large data.
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Acknowledgement
This work was supported in part by the National Natural Science Foundation of China under Grants U20B2067, 61790552, 61790554, and in part by the Innovation Foundation for Doctor Dissertation of Northwestern Polytechnical University under Grant CX201953.
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Zhang, Z., Martin, A., Liu, Z., Zhou, K., Zhang, Y. (2021). Fast Unfolding of Credal Partitions in Evidential Clustering. In: Denœux, T., Lefèvre, E., Liu, Z., Pichon, F. (eds) Belief Functions: Theory and Applications. BELIEF 2021. Lecture Notes in Computer Science(), vol 12915. Springer, Cham. https://doi.org/10.1007/978-3-030-88601-1_1
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DOI: https://doi.org/10.1007/978-3-030-88601-1_1
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