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A semisupervised learning model based on fuzzy min–max neural networks for data classification
journal contribution
posted on 2021-11-01, 00:00 authored by F Pourpanah, D Wang, R Wang, Chee Peng LimChee Peng LimA semisupervised learning model based on fuzzy min–max neural networks for data classification
History
Journal
Applied Soft ComputingVolume
112Article number
ARTN 107856Pagination
1 - 15Publisher
ElsevierLocation
Amsterdam, The NetherlandsPublisher DOI
ISSN
1568-4946eISSN
1872-9681Language
EnglishPublication classification
C1 Refereed article in a scholarly journalUsage metrics
Categories
Keywords
ARCHITECTUREARTMAPBRAIN STORM OPTIMIZATIONComputer ScienceComputer Science, Artificial IntelligenceComputer Science, Interdisciplinary ApplicationsData classificationFEATURE-SELECTIONFuzzy min-max neural networksHuman motion recognitionHYBRID MODELIncremental learningRULEScience & TechnologySemisupervised learningTechnologyInformation SystemsArtificial Intelligence and Image Processing
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