Data stream is a newly emerging data model for applications like environment monitoring, Web click stream, network traffic monitoring, etc. It consists of an infinite sequence of d...
In this paper we report about an investigation in which we studied the properties of Bayes' inferred neural network classifiers in the context of outlier detection. The proble...
Fraud detection is of great importance to financial institutions. This paper is concerned with the problem of finding outliers in time series financial data using Peer Group Analy...
Efficiently detecting outliers or anomalies is an important problem in many areas of science, medicine and information technology. Applications range from data cleaning to clinica...
Matthew Eric Otey, Amol Ghoting, Srinivasan Partha...
This work addresses the problem of feature extraction for boosting the performance of outlier detectors in high-dimensional spaces. Recent years have observed the prominence of mu...