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.
Trimmed fuzzy clustering for interval-valued data / De Giovanni, Livia; P., D'Urso; R., Massari. - In: ADVANCES IN DATA ANALYSIS AND CLASSIFICATION. - ISSN 1862-5347. - 9:1(2015), pp. 21-40. [10.1007/s11634-014-0169-3]
Trimmed fuzzy clustering for interval-valued data
DE GIOVANNI, LIVIA;
2015
Abstract
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.
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