A Mixture Approach to Novelty Detection Using Training Data with Outliers-Reference-Cited by-同舟云学术

A Mixture Approach to Novelty Detection Using Training Data with Outliers

Published:2001 Issue: Volume: Page:300-311
ISSN:0302-9743
Container-title:Machine Learning: ECML 2001
language:
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Author:

Lauer Martin

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/3-540-44795-4_26

Reference16 articles.

1. Vic Barnett and Toby Lewis. Outliers in Statistical Data. John Wiley & Sons, 1978.

2. Colin Campbell and Kristin P. Bennett. A linear programming approach to novelty detection. In Advances in Neural Information Processing Systems 13 (to appear), 2001.

3. L. H. Cox, M. M. Johnson, and K. Kafadar. Exposition of statistical graphics technology. In ASA Proceedings of the Statistical Computation Section, pages 55–56, 1982.

4. A. P. Dempster, N. M. Laird, and D. B. Rubin. Maximum likelihood from incomplete data via the EM algorithm. Journal of the Royal Statistical Society Series B, 39:1–38, 1977.

5. Jean Diebolt and Christian P. Robert. Estimation of finite mixtures through bayesian sampling. Journal of the Royal Statistical Society Series B, 56(2):363–375, 1994.

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