Similarity classifier with OWA operators
Toolbox presents vector based classification method which uses similarity measures and OWA operators
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Similarity classifier with OWA operators toolbox presents vector based classification method which uses similarity measures and OWA operators to make a distiction to which class samples belong. It creates ideal vectors for each class and then uses similarity to measure how similar the samples are compared to each ideal vector. These similarity vectors are then aggregated by OWA operators. For more information about the method see the original publication:
P. Luukka, O. Kurama, Similarity classifier with ordered weighted averaging operators,
Expert Systems With Applications, 40, (2013), pp. 995-1002
Cite As
Pasi Luukka (2026). Similarity classifier with OWA operators (https://www.mathworks.com/matlabcentral/fileexchange/38871-similarity-classifier-with-owa-operators), MATLAB Central File Exchange. Retrieved .
General Information
- Version 1.1.0.0 (12.5 KB)
MATLAB Release Compatibility
- Compatible with any release
Platform Compatibility
- Windows
- macOS
- Linux
