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.
De Giovanni, Livia; P., D'Urso; R., Massari. (2015). Trimmed fuzzy clustering for interval-valued data. ADVANCES IN DATA ANALYSIS AND CLASSIFICATION, (ISSN: 1862-5347), 9:1, 21-40. Doi: 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.
| File | Dimensione | Formato | |
|---|---|---|---|
|
2015ADAC.pdf
Solo gestori archivio
Tipologia:
Versione dell'editore
Licenza:
DRM (Digital rights management) non definiti
Dimensione
347.67 kB
Formato
Adobe PDF
|
347.67 kB | Adobe PDF | Visualizza/Apri |
Pubblicazioni consigliate
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
