Chapter

Data Warehousing and Knowledge Discovery

Volume 2454 of the series Lecture Notes in Computer Science pp 170-180

Date:

Outlier Detection Using Replicator Neural Networks

  • Simon HawkinsAffiliated withCSIRO Mathematical and Information Sciences
  • , Hongxing HeAffiliated withCSIRO Mathematical and Information Sciences
  • , Graham WilliamsAffiliated withCSIRO Mathematical and Information Sciences
  • , Rohan BaxterAffiliated withCSIRO Mathematical and Information Sciences

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Abstract

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.