Peer Group Analysis – Local Anomaly Detection in Longitudinal Data (2007)
Peer group analysis is a new tool for monitoring behavior over time in data mining situations. In particular, the tool detects individual objects that begin to behave in a way distinct from objects...
David Hand And, Richard J. Bolton, David J. H, Martin Crowder
In this paper we consider the question of uncertainty of discovered patterns in data mining. In particular, we develop statistical tests for flagged patterns found in continuous data, where such...
Projection techniques for nonlinear principal component analysis (2003)
Richard J. Bolton, David J. H, Andrew R. Webb
Principal Components Analysis (PCA) is traditionally a linear technique for projecting multidimensional data onto lower dimensional subspaces with minimal loss of variance. However, there are several...
Statistical Fraud Detection: A Review (2002)
Bolton, Richard J., Hand, David J.
Fraud is increasing dramatically with the expansion of modern technology and the global superhighways of communication, resulting in the loss of billions of dollars worldwide each year. Although...
Statistical Fraud Detection: A Review (2002)
Richard J. Bolton, David J. Hand, David J. H
Fraud is increasing dramatically with the expansion of modern technology and the global superhighways of communication, resulting in the loss of billions of dollars worldwide each year. Although...
Statistical fraud detection: A review (2002)
Abstract. Fraud is increasing dramatically with the expansion of modern technology and the global superhighways of communication, resulting in the loss of billions of dollars worldwide each year....
Unsupervised profiling methods for fraud detection, Credit Scoring and Credit Control VII (2001)
Credit card fraud falls broadly into two categories: behavioural fraud and application fraud. Application fraud occurs when individuals obtain new credit cards from issuing companies using false...
A Characterization of Principal Components for Projection Pursuit (1999)
Richard J. Bolton, Wojtek J. Krzanowski
Principal Component Analysis is a technique often found to be useful for identifying structure in multivariate data. Although it has various characterizations (Rao 1964), the most familiar is as a...