Obtaining a fuzzy classification rule system from a non-supervised clustering
Hasperué, Waldo
Obtaining a fuzzy classification rule system from a non-supervised clustering - ref_localidad@NULL : IEEE, 2008 - 1 archivo (126,5 kB)
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.
DIF005993
LÓGICA DIFUSA
REDES NEURONALES
Obtaining a fuzzy classification rule system from a non-supervised clustering - ref_localidad@NULL : IEEE, 2008 - 1 archivo (126,5 kB)
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.
DIF005993
LÓGICA DIFUSA
REDES NEURONALES