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首页> 外文期刊>IEE Proceedings. Part A >Extreme value statistics for novelty detection in biomedical data processing
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Extreme value statistics for novelty detection in biomedical data processing

机译:用于生物医学数据处理中新颖性检测的极值统计

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摘要

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 we 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.
机译:极值理论(EVT)是统计的一个分支,它涉及异常低值或高值数据的分布,即在某些分布的尾部。这些极值点在许多应用中都很重要,因为它们代表正常事件的外围区域,我们可能希望根据这些区域来定义新颖事件。这种新颖性检测方法的使用对于分析数据非常有用,例如,在医学筛查中,某些重要类别的示例很少存在。结果表明,可以使用极值统计来采取新颖性检测问题的原则方法。

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