Authors: Anna Bartkowiak
Addresses: Institute of Computer Science, University of Wroclaw, Joliot Curie 15, 50-383 Wroclaw, Poland; Wroclaw High School of Applied Informatics, Wejherowska 28, 54-239 Wroclaw, Poland
Abstract: Nowadays a huge amount of data is gathered in the biometric area, e.g., sequences of DNA code, graphical images for recognition or authorisation of subjects, video monitoring, clinical trials or health care. Outliers are observations which are discordant with the model describing the data. The appearance of an outlier may be caused by a gross error; alternatively, an outlier (or a group of them) may represent observations which are caused by phenomena not accounted for in the assumed model. The paper shows a subjective survey of some methods serving for detection of outliers or anomalies in multivariate data. The methods are viewed from historical perspective.
Keywords: outliers; biometrical data; anomalies; robust; atypical; graphical visualisation; large data sets; biometrics; multivariate data.
International Journal of Biometrics, 2010 Vol.2 No.1, pp.2 - 18
Published online: 15 Dec 2009 *Full-text access for editors Access for subscribers Purchase this article Comment on this article