A novel Matlab routine, called FKML0, is proposed to implement a variant of the standard Fuzzy K-Means algorithm. Such a variant allows for sparsity in the fuzzy membership degree matrix by adding a suitable regularization term based on the L0 norm to the Fuzzy K-Means loss function. The new clustering algorithm, called Fuzzy K-Means with L0 regularization, is able to assign, on the one hand, objects clearly belonging to a cluster with membership degrees equal to 1 (and 0 elsewhere) and, on the other hand, objects with unclear assignment with fuzzy membership degrees in the interval [0,1].

FKML0: A Matlab Routine for Sparse Fuzzy Clustering / Ferraro, Maria Brigida; Forti, Marco; Giordani, Paolo. - 8:(2024), pp. 1-8. (Intervento presentato al convegno 2024 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) tenutosi a Yokohama, Japan) [10.1109/fuzz-ieee60900.2024.10611853].

FKML0: A Matlab Routine for Sparse Fuzzy Clustering

Ferraro, Maria Brigida;Forti, Marco;Giordani, Paolo
2024

Abstract

A novel Matlab routine, called FKML0, is proposed to implement a variant of the standard Fuzzy K-Means algorithm. Such a variant allows for sparsity in the fuzzy membership degree matrix by adding a suitable regularization term based on the L0 norm to the Fuzzy K-Means loss function. The new clustering algorithm, called Fuzzy K-Means with L0 regularization, is able to assign, on the one hand, objects clearly belonging to a cluster with membership degrees equal to 1 (and 0 elsewhere) and, on the other hand, objects with unclear assignment with fuzzy membership degrees in the interval [0,1].
2024
2024 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
matlab; clustering; Fuzzy K-Means; sparsity; L0 regularization
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
FKML0: A Matlab Routine for Sparse Fuzzy Clustering / Ferraro, Maria Brigida; Forti, Marco; Giordani, Paolo. - 8:(2024), pp. 1-8. (Intervento presentato al convegno 2024 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) tenutosi a Yokohama, Japan) [10.1109/fuzz-ieee60900.2024.10611853].
File allegati a questo prodotto
File Dimensione Formato  
Ferraro_FKML0_2024.pdf

solo gestori archivio

Tipologia: Versione editoriale (versione pubblicata con il layout dell'editore)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 3.42 MB
Formato Adobe PDF
3.42 MB Adobe PDF   Contatta l'autore

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1723144
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? 0
social impact