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A Comparative Study of RNN for Outlier Detection in Data Mining

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Lifang GuAuthors Info & Claims

ICDM '02: Proceedings of the 2002 IEEE International Conference on Data Mining

Page 709

Published: 09 December 2002 Publication History

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Abstract

We have proposed replicator neural networks (RNNs)for outlier detection [8]. Here we compare RNN for outlierdetection with three other methods using both publiclyavailable statistical datasets (generally small) and datamining datasets (generally much larger and generally realdata). The smaller datasets provide insights into the relativestrengths and weaknesses of RNNs. The larger datasetsparticularly test scalability and practicality of application.

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A Comparative Study of RNN for Outlier Detection in Data Mining
1. Information systems
  1. Information systems applications
    1. Data mining

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ICDM '02: Proceedings of the 2002 IEEE International Conference on Data Mining

December 2002

ISBN:0769517544

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IEEE Computer Society

United States

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Published: 09 December 2002

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Park DKim HKemp C(2019)Multimodal anomaly detection for assistive robotsAutonomous Robots10.1007/s10514-018-9733-643:3(611-629)Online publication date: 1-Mar-2019
https://dl.acm.org/doi/10.1007/s10514-018-9733-6
Kim JKim HKim H(2019)Fraud detection for job placement using hierarchical clusters-based deep neural networksApplied Intelligence10.1007/s10489-019-01419-249:8(2842-2861)Online publication date: 1-Aug-2019
https://dl.acm.org/doi/10.1007/s10489-019-01419-2
Lasserre JPauwels E(2019)The empirical Christoffel function with applications in data analysisAdvances in Computational Mathematics10.1007/s10444-019-09673-145:3(1439-1468)Online publication date: 1-Jun-2019
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Nazari ZYu SKang DKawachi Y(2018)Comparative Study of Outlier Detection Algorithms for Machine LearningProceedings of the 2018 2nd International Conference on Deep Learning Technologies10.1145/3234804.3234817(47-51)Online publication date: 27-Jun-2018
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