Statistical Approaches to Detect Anomalies-Reference-Cited by-同舟云学术

Statistical Approaches to Detect Anomalies

Published:2020 Issue: Volume: Page:499-509
ISSN:2194-5357
Container-title:Emerging Research in Data Engineering Systems and Computer Communications
language:
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Author:

Madhuri G. Sandhya,Usha Rani M.

Publisher

Springer Singapore

Link

http://link.springer.com/content/pdf/10.1007/978-981-15-0135-7_46

Reference8 articles.

1. Chandola, V., Banerjee, A., Kumar, V.: Anomaly detection: a survey. ACM Comput. Surv. 41(3) (2009)

2. Goldstein, M., Uchida, S.: A comparative evaluation of unsupervised anomaly detection algorithms for multivariate data. PLoS ONE 11(4), 31 (2016)

3. Markou, M., Singh, S.: Novelty detection: a review—part 1: statistical approaches. Sig. Process. 83(12), 2481–2497 (2003)

4. Hawkins, J., Ahmad, S., Lavin, A.: Biological and Machine Intelligence. Available at: http://bit.ly/2qJzvjO (2016)

5. P-N Tan.: Introduction to “Data Mining”, Michigan State University, Michael Steinbach, University of Minnesota, Vipin Kumar, University of Minnesota and Army High Performance Computing Research Center

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