The Benefits of Modeling Slack Variables in SVMs

DOI10.1162/NECO_a_00714zbMath1473.68172OpenAlexW2087095155WikidataQ47671256 ScholiaQ47671256MaRDI QIDQ5380231

Pedro Antonio Gutiérrez, Fengzhen Tang, Huanhuan Chen, Peter Tiňo

Publication date: 4 June 2019

Published in: Neural Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1162/neco_a_00714

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Uses Software

• UCI-ml
• LIBSVM

Cites Work

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• A new learning paradigm: learning using privileged information
• Adaptive Metric Learning Vector Quantization for Ordinal Classification
• Reduction from Cost-Sensitive Ordinal Ranking to Weighted Binary Classification
• Exploitation of Pairwise Class Distances for Ordinal Classification

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