An explainable semi-supervised self-organizing fuzzy inference system for streaming data classification

DOI10.1016/J.INS.2021.11.047OpenAlexW3216150967MaRDI QIDQ6188185

Xiaowei Gu

Publication date: 1 February 2024

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://kar.kent.ac.uk/91573/1/S3OFIS%2B_accepted.pdf

zbMATH Keywords

semi-supervised learningdata stream classificationevolving intelligent systempseudo-labelling

Mathematics Subject Classification ID

Computational learning theory (68Q32) Learning and adaptive systems in artificial intelligence (68T05) Fuzzy analysis in statistics (62A86) Computational aspects of data analysis and big data (68T09)

Cites Work

• Unnamed Item
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• A self-trained ensemble with semisupervised SVM: an application to pixel classification of remote sensing imagery
• Evolving fuzzy classifiers using different model architectures
• An approach for on-line extraction of fuzzy rules using a self-organising fuzzy neural network
• Self-organising fuzzy logic classifier
• A survey on semi-supervised learning
• Sequential adaptive fuzzy inference system (SAFIS) for nonlinear system identification and prediction
• Modeling the shape of the scene: A holistic representation of the spatial envelope

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