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 LimA semisupervised learning model based on fuzzy min–max neural networks for data classification
History
Journal
Applied Soft ComputingVolume
112Article number
ARTN 107856Pagination
1 - 15Location
Amsterdam, The NetherlandsPublisher DOI
ISSN
1568-4946eISSN
1872-9681Language
EnglishPublication classification
C1 Refereed article in a scholarly journalPublisher
ELSEVIERUsage metrics
Categories
Keywords
Science & TechnologyTechnologyComputer Science, Artificial IntelligenceComputer Science, Interdisciplinary ApplicationsComputer ScienceSemisupervised learningData classificationIncremental learningFuzzy min-max neural networksHuman motion recognitionBRAIN STORM OPTIMIZATIONFEATURE-SELECTIONHYBRID MODELARTMAPARCHITECTURERULE4611 Machine learning
Licence
Exports
RefWorks
BibTeX
Ref. manager
Endnote
DataCite
NLM
DC