Advantages of unbiased support vector classifiers for data mining applications

DOI10.1023/B:VLSI.0000027487.93757.91zbMath1101.68778MaRDI QIDQ2386725

Aníbal R. Figueiras-Vidal, Fernando Pérez-Cruz, Ángel Navia-Vázquez, Antonio Artés-Rodríguez

Publication date: 25 August 2005

Published in: Journal of VLSI Signal Processing Systems for Signal, Image, and Video Technology (Search for Journal in Brave)

zbMATH Keywords

classifierdata miningweighted least squaresempirical risk minimizationunbiasedsupport vectorerror count

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Pattern recognition, speech recognition (68T10)

Related Items (2)

An unbiased LSSVM model for classification and regression ⋮ Online chaotic time series prediction using unbiased composite kernel machine via Cholesky factorization

This page was built for publication: Advantages of unbiased support vector classifiers for data mining applications