DocumentCode :
1433124
Title :
Extreme value statistics for novelty detection in biomedical data processing
Author :
Roberts, S.J.
Author_Institution :
Dept. of Eng. Sci., Oxford Univ., UK
Volume :
147
Issue :
6
fYear :
2000
fDate :
11/1/2000 12:00:00 AM
Firstpage :
363
Lastpage :
367
Abstract :
Extreme value theory (EVT) is a branch of statistics which concerns the distributions of data of unusually low or high value i.e. in the tails of some distribution. These extremal points are important in many applications as they represent the outlying regions of normal events against which one may wish to define novel events. The use of such novelty detection approaches is useful for analysis of data for which few exemplars of some important class exist, for example in medical screening. It is shown that a principled approach to the issue of novelty detection may be taken using extreme value statistics
Keywords :
medical signal detection; medical signal processing; statistical analysis; biomedical data processing; data distributions; distribution tails; extreme value statistics; normal events; novelty detection; outlying regions; unusually high value; unusually low value;
fLanguage :
English
Journal_Title :
Science, Measurement and Technology, IEE Proceedings -
Publisher :
iet
ISSN :
1350-2344
Type :
jour
DOI :
10.1049/ip-smt:20000841
Filename :
899992
Link To Document :
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