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Signal processing / Multivariate statistics / Support vector machine / Supervised learning / Kernel trick / Kernel / Pattern recognition / Mode / Gaussian function / Statistics / Machine learning / Statistical classification


S.A. Solla, T.K. Leen and K.-R. Muller ¨ (eds.), 582–588 MIT Press[removed]Support Vector Method for Novelty Detection
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Document Date: 2005-03-22 08:33:45

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Microsoft Research Ltd. / MIT Press / Data domain / AAAI Press / 8D / /

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Australian National University / University of London / /

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MIT / Australian National University / Canberra / U.S. Securities and Exchange Commission / UK Department of Engineering / University of London / /

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John Shawe-Taylor / C. Bishop / Robert Williamsonx / John Platt / M. Lindenbaum / Bernhard Sch¨olkopf / Williamson / S. Ben-David / C. Schn¨orr / Unsupervised Learning / Alex Smolax / M. Tipping / /

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corresponding algorithm / vector algorithm / proposed algorithm / concrete algorithm / Clustering algorithms / 2 ALGORITHMS / Data Mining / /

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