Unsupervised Fuzzy eIX: Evolving Internal-eXternal Fuzzy Clustering

Charles Aguiar, Daniel Leite

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

8 Citas (Scopus)

Resumen

Time-varying classifiers, namely, evolving classifiers, play an important role in a scenario in which information is available as a never-ending online data stream. We present a new unsupervised learning method for numerical data called evolving Internal-eXternal Fuzzy clustering method (Fuzzy eIX). We develop the notion of double-boundary fuzzy granules and elaborate on its implications. Type 1 and type 2 fuzzy inference systems can be obtained from the projection of Fuzzy eIX granules. We perform the principle of the balanced information granularity within Fuzzy eIX classifiers to achieve a higher level of model understandability. Internal and external granules are updated from a numerical data stream at the same time that the global granular structure of the classifier is autonomously evolved. A synthetic nonstationary problem called Rotation of Twin Gaussians shows the behavior of the classifier. The Fuzzy eIX classifier could keep up with its accuracy in a scenario in which offline-trained classifiers would clearly have their accuracy drastically dropped.

Idioma originalInglés
Título de la publicación alojada2020 IEEE International Conference on Evolving and Adaptive Intelligent Systems, EAIS 2020 - Proceedings
EditoresGiovanna Castellano, Ciro Castiello, Corrado Mencar
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)9781728143842
DOI
EstadoPublicada - may. 2020
Publicado de forma externa
Evento12th IEEE International Conference on Evolving and Adaptive Intelligent Systems, EAIS 2020 - Bari, Italia
Duración: 27 may. 202029 may. 2020

Serie de la publicación

NombreIEEE Conference on Evolving and Adaptive Intelligent Systems
Volumen2020-May
ISSN (versión impresa)2330-4863
ISSN (versión digital)2473-4691

Conferencia

Conferencia12th IEEE International Conference on Evolving and Adaptive Intelligent Systems, EAIS 2020
País/TerritorioItalia
CiudadBari
Período27/05/2029/05/20

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