Possibilistic classification learning based on contrastive loss in learning vector quantizer networks

DOI10.1007/978-3-030-87986-0_14zbMath1497.68434OpenAlexW3204499579MaRDI QIDQ2148708

Seyedfakhredin Musavishavazi, Marika Kaden, Thomas Villmann

Publication date: 24 June 2022

Full work available at URL: https://doi.org/10.1007/978-3-030-87986-0_14

zbMATH Keywords

multiple classificationLVQinterpretable modelscontrastive learning (CL)RSLVQ

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Learning and adaptive systems in artificial intelligence (68T05)

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