Information technologies and computer sciences
Comparison of learning criteria for fuzzy classifier
Keywords
classification
fuzzy knowledge base
learning
Abstract
A new criterion for fuzzy classifier learning is proposed. The proposed criterion inherits the advantages of well-known learning criteria: misclassification rate and distance between fuzzy sets. Executed experiments show that learning with proposed criterion produces the fuzzy classifiers with the best misclassification rate.
How to Cite
[1]
“Comparison of learning criteria for fuzzy classifier”, Вісник ВПІ, no. 6, pp. 84–91, Nov. 2010, Accessed: Nov. 15, 2026. Available: https://vpi.sprava.net/index.php/visnyk/article/view/539
