About: Self-organizing fuzzy inference ensemble system for big streaming data classification

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type	http://eprints.org/ontology/ArticleEPrint http://eprints.org/ontology/EPrint Article Academic Article
seeAlso	HTML Summary of #90374 Self-organizing fuzzy inference ensemble system for big streaming data classification
sameAs	Self-organizing fuzzy inference ensemble system for big streaming data classification
Title	Self-organizing fuzzy inference ensemble system for big streaming data classification
described by	https://demo.openlinksw.com/about/id/entity/https/www.cs.kent.ac.uk/people/staff/akj22/materials/CO644/export_kar_RDFN3.n3
Date	2021-04-22
Creator	Plamen Angelov Zhijin Zhao Xiaowei Gu
status	peer reviewed published
Publisher	Elsevier
abstract	An evolving intelligent system (EIS) is able to self-update its system structure and meta-parameters from streaming data. However, since the majority of EISs are implemented on a single-model architecture, their performances on large-scale, complex data streams are often limited. To address this deficiency, a novel self-organizing fuzzy inference ensemble framework is proposed in this paper. As the base learner of the proposed ensemble system, the self-organizing fuzzy inference system is capable of self-learning a highly transparent predictive model from streaming data on a chunk-by-chunk basis through a human-interpretable process. Very importantly, the base learner can continuously self-adjust its decision boundaries based on the inter-class and intra-class distances between prototypes identified from successive data chunks for higher classification precision. Thanks to its parallel distributed computing architecture, the proposed ensemble framework can achieve great classification precision while maintain high computational efficiency on large-scale problems. Numerical examples based on popular benchmark big data problems demonstrate the superior performance of the proposed approach over the state-of-the-art alternatives in terms of both classification accuracy and computational efficiency.
Is Part Of	Knowledge-Based Systems https://kar.kent.ac.uk/id/repository
Subject	QA 75 Electronic computers. Computer science
list of authors	https://kar.kent.ac.uk/id/eprint/90374#authors
volume	218
is topic of	https://www.cs.kent.ac.uk/people/staff/akj22/materials/CO644/export_kar_RDFN3.n3
is primary topic of	HTML Summary of #90374 Self-organizing fuzzy inference ensemble system for big streaming data classification

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