Trimmed fuzzy clustering for interval-valued data. (English) Zbl 1414.62242

Summary: In this paper, following a partitioning around medoids approach, a fuzzy clustering model for interval-valued data, i.e., FCMd-ID, is introduced. Successively, for avoiding the disruptive effects of possible outlier interval-valued data in the clustering process, a robust fuzzy clustering model with a trimming rule, called Trimmed Fuzzy \(C\)-medoids for interval-valued data (TrFCMd-ID), is proposed. In order to show the good performances of the robust clustering model, a simulation study and two applications are provided.


62H30 Classification and discrimination; cluster analysis (statistical aspects)
62G35 Nonparametric robustness
03E72 Theory of fuzzy sets, etc.
62A86 Fuzzy analysis in statistics


Full Text: DOI


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