Neuro-fuzzy approach to processing inputs with missing values in pattern recognition problems.
type: Item
instance of: scholarly article
title: Neuro-fuzzy approach to processing inputs with missing values in pattern recognition problems.
zbMATH Open document ID: 1033.68093
DOI: 10.1016/S0888-613X(02)00070-1
author: Bogdan Gabrys
published in: International Journal of Approximate Reasoning
publication date: 2003-07-30T00:00:00Z
Mathematics Subject Classification ID: 68T10
zbMATH DE Number: 1956975
zbMATH Keywords: Missing data
zbMATH Keywords: neuro-fuzzy classifier
zbMATH Keywords: pattern recognition
zbMATH Keywords: fuzzy systems
MaRDI profile type: Publication
cites work: Missing Values and Learning of Fuzzy Rules
cites work: Q4490109
cites work: Learning hybrid neuro-fuzzy classifier models from data: to combine or not to combine?
cites work: Agglomerative learning algorithms for general fuzzy Min-Max neural network
cites work: Classification of Incomplete Pattern Vectors Using Modified Discrminant Functions
cites work: Fuzzy classifier design
cites work: Q3816821
cites work: Q4210639
cites work: Q4861400
cites work: Q4246485
cites work: Q4131415
full work available at URL: s0888-613x(02)00070-1
OpenAlex ID: W2122752936
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description: scientific article; zbMATH DE number 1956975