Obtaining a fuzzy classification rule system from a non-supervised clustering
Material type:
ArticleDescription: 1 archivo (126,5 kB)Subject(s): Online resources: Summary: The fuzzy classification systems have been broadly used to solve control and decision- making problem. However, its design is complex, even when having a human expert assistance. This paper presents a new strategy capable of automatically defining the corresponding Fuzzy Classification Rule System from a non- supervised clustering of the available data. Its application to three data sets of the UCI repository has given quite satisfactory results.
| Item type | Home library | Collection | Call number | URL | Status | Date due | Barcode | |
|---|---|---|---|---|---|---|---|---|
Capítulo de libro
|
Biblioteca de la Facultad de Informática | Biblioteca digital | A0341 (Browse shelf(Opens below)) | Link to resource | No corresponde |
Formato de archivo: PDF. -- Este documento es producción intelectual de la Facultad de Informática - UNLP (Colección BIPA/Biblioteca)
The fuzzy classification systems have been broadly used to solve control and decision- making problem. However, its design is complex, even when having a human expert assistance. This paper presents a new strategy capable of automatically defining the corresponding Fuzzy Classification Rule System from a non- supervised clustering of the available data. Its application to three data sets of the UCI repository has given quite satisfactory results.
International Conference on Information Technology Interfaces, 2008. ITI 2008 (30ª : 2008, Jun. 23-26 : Dubrovnik, Croacia), IEEE. 2008. pp.341-346