Unsupervised Fuzzy eIX: Evolving Internal-eXternal Fuzzy Clustering

Charles Aguiar, Daniel Leite

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

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.

Original languageEnglish
Title of host publication2020 IEEE International Conference on Evolving and Adaptive Intelligent Systems, EAIS 2020 - Proceedings
EditorsGiovanna Castellano, Ciro Castiello, Corrado Mencar
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728143842
DOIs
StatePublished - May 2020
Externally publishedYes
Event12th IEEE International Conference on Evolving and Adaptive Intelligent Systems, EAIS 2020 - Bari, Italy
Duration: 27 May 202029 May 2020

Publication series

NameIEEE Conference on Evolving and Adaptive Intelligent Systems
Volume2020-May
ISSN (Print)2330-4863
ISSN (Electronic)2473-4691

Conference

Conference12th IEEE International Conference on Evolving and Adaptive Intelligent Systems, EAIS 2020
Country/TerritoryItaly
CityBari
Period27/05/2029/05/20

Keywords

  • Evolving Fuzzy System
  • Granular Computing
  • Online Data Stream
  • Unsupervised Learning

Fingerprint

Dive into the research topics of 'Unsupervised Fuzzy eIX: Evolving Internal-eXternal Fuzzy Clustering'. Together they form a unique fingerprint.

Cite this