Novelty detection employing an L-2 optimal non-parametric density estimator.
PATTERN RECOGN LETT
This paper considers the application of a recently proposed L, optimal non-parametric reduced set density estimator to novelty detection and binary classification and provides empirical comparisons with other forms of density estimation as well as support vector machines. (C) 2004 Elsevier B.V. All rights reserved.
|Title:||Novelty detection employing an L-2 optimal non-parametric density estimator|
|Keywords:||reduced set density estimator (RSDE), novelty detection, binary classification, SUPPORT|
|UCL classification:||UCL > School of BEAMS > Faculty of Maths and Physical Sciences
UCL > School of BEAMS > Faculty of Maths and Physical Sciences > Statistical Science
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