General support vector representation machine for one-class classification of non-stationary classes

DOI10.1016/J.PATCOG.2008.04.001zbMath1151.68601OpenAlexW2077989092MaRDI QIDQ936411

Fatih Camci, Ratna Babu Chinnam

Publication date: 13 August 2008

Published in: Pattern Recognition (Search for Journal in Brave)

Full work available at URL: http://dspace.lib.cranfield.ac.uk/handle/1826/6868

zbMATH Keywords

non-stationary processessupport vector machineoutlier detectionone-class classificationnovelty detectiononline trainingnon-stationary classes

Mathematics Subject Classification ID

Pattern recognition, speech recognition (68T10)

Related Items (2)

Approximate polytope ensemble for one-class classification ⋮ Evolutionary sampling: a novel way of machine learning within a probabilistic framework

Cites Work

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• Novelty detection: a review. II. Neural network based approaches
• Robust kernel distance multivariate control chart using support vector principles
• On the Choice of Smoothing Parameters for Parzen Estimators of Probability Density Functions
• A kernel-distance-based multivariate control chart using support vector methods

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