@inproceedings{1093d88ae8154e55a985929d67dd8cb1,
title = "Ensemble algorithms for unsupervised anomaly detection",
abstract = "Many anomaly detection algorithms have been proposed in recent years, including density-based and rank-based algorithms. In this paper, we propose ensemble methods to improve the performance of these individual algorithms. We evaluate approaches that use score and rank aggregation for these algorithms. We also consider sequential methods in which one detection method is followed by the other. We use several datasets to evaluate the performance of the proposed ensemble methods. Our results show that sequential methods significantly improve the ability to detect anomalous data points.",
keywords = "Anomaly detection, Density-based anomaly detection, Ensemble method, Rank-based anomaly detection",
author = "Zhiruo Zhao and Mehrotra, {Kishan G.} and Mohan, {Chilukuri K.}",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2015.; 28th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2015 ; Conference date: 10-06-2015 Through 12-06-2015",
year = "2015",
doi = "10.1007/978-3-319-19066-2_50",
language = "English (US)",
isbn = "9783319190655",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "514--525",
editor = "Chang-Hwan Lee and Yongdai Kim and Kwon, {Young Sig} and Juntae Kim and Moonis Ali",
booktitle = "Current Approaches in Applied Artificial Intelligence - 28th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2015, Proceedings",
}