Evolving fuzzy classifiers using different model architectures
type: Item
instance of: scholarly article
title: Evolving fuzzy classifiers using different model architectures
zbMATH Open document ID: 1186.68404
author: N. E. Zubov
published in: Fuzzy Sets and Systems
publication date: 2009-08-28T00:00:00Z
Mathematics Subject Classification ID: 68T10
Mathematics Subject Classification ID: 68T05
zbMATH DE Number: 5599510
zbMATH Keywords: fuzzy rule-based classifiers
zbMATH Keywords: evolving Takagi-Sugeno systems
zbMATH Keywords: on-line and incremental learning
zbMATH Keywords: global and local learning
zbMATH Keywords: concept drift
zbMATH Keywords: outlier treatment
zbMATH Keywords: on-line image classification
describes a project that uses: ElemStatLearn
describes a project that uses: NEFCLASS-X
MaRDI profile type: Publication
full work available at URL: j.fss.2008.06.019
OpenAlex ID: W2092682490
cites work: Evolving rule-based models. A tool for design of flexible adaptive systems.
cites work: An approach for fuzzy rule-base adaptation using on-line clustering
cites work: Problems of identification and control
cites work: The elements of statistical learning. Data mining, inference, and prediction
cites work: Extensions of vector quantization for incremental clustering
cites work: Fuzzy identification of systems and its applications to modeling and control
cites work: Q4833828
DOI: 10.1016/J.FSS.2008.06.019
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description: scientific article; zbMATH DE number 5599510