Title :
Extreme value statistics for novelty detection in biomedical data processing
Author_Institution :
Dept. of Eng. Sci., Oxford Univ., UK
fDate :
11/1/2000 12:00:00 AM
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;
Journal_Title :
Science, Measurement and Technology, IEE Proceedings -
DOI :
10.1049/ip-smt:20000841