Neuro-fuzzy approach to processing inputs with missing values in pattern recognition problems.
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Publication:1399486
DOI10.1016/S0888-613X(02)00070-1zbMath1033.68093OpenAlexW2122752936MaRDI QIDQ1399486
Publication date: 30 July 2003
Published in: International Journal of Approximate Reasoning (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/s0888-613x(02)00070-1
Related Items (4)
Combining labelled and unlabelled data in the design of pattern classification systems ⋮ Learning hybrid neuro-fuzzy classifier models from data: to combine or not to combine? ⋮ The design of granular classifiers: A study in the synergy of interval calculus and fuzzy sets in pattern recognition ⋮ Learn\(^{++}\).MF: A random subspace approach for the missing feature problem
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- Agglomerative learning algorithms for general fuzzy Min-Max neural network
- Learning hybrid neuro-fuzzy classifier models from data: to combine or not to combine?
- Classification of Incomplete Pattern Vectors Using Modified Discrminant Functions
- Missing Values and Learning of Fuzzy Rules
- Fuzzy classifier design
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