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Constructing boosting algorithms from SVMs: an application to one-class classification

Raetsch, Gunnar; Mika, Sebastian; Schoelkopf, Bernhard; Mueller, Klaus-Robert

Description

We show via an equivalence of mathematical programs that a support vector (SV) algorithm can be translated into an equivalent boosting-like algorithm and vice versa. We exemplify this translation procedure for a new algorithm-one-class leveraging-starting from the one-class support vector machine (1-SVM). This is a first step toward unsupervised learning in a boosting framework. Building on so-called barrier methods known from the theory of constrained optimization, it returns a function,...[Show more]

CollectionsANU Research Publications
Date published: 2002
Type: Journal article
URI: http://hdl.handle.net/1885/75003
Source: IEEE Transactions on Pattern Analysis and Machine Intelligence
DOI: 10.1109/TPAMI.2002.1033211

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