Outlier Detection Using Replicator Neural Networks

We consider the problem of finding outliers in large multivariate databases. Outlier detection can be applied during the data cleansing process of data mining to identify problems with the data itself, and to fraud detection where groups of outliers are often of particular interest. We use replicato...

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Hauptverfasser: Hawkins, Simon, He, Hongxing, Williams, Graham, Baxter, Rohan
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Baxter, Rohan
description We consider the problem of finding outliers in large multivariate databases. Outlier detection can be applied during the data cleansing process of data mining to identify problems with the data itself, and to fraud detection where groups of outliers are often of particular interest. We use replicator neural networks (RNNs) to provide a measure of the outlyingness of data records. The performance of the RNNs is assessed using a ranked score measure. The effectiveness of the RNNs for outlier detection is demonstrated on two publicly available databases.
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subjects Applied sciences
Computer science
control theory
systems
Exact sciences and technology
Fraud Detection
Hide Layer
Information systems. Data bases
Memory organisation. Data processing
Network Intrusion Detection
Outlier Detection
Outlier Detection Method
Software
title Outlier Detection Using Replicator Neural Networks
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