Extending the generalised Pareto distribution for novelty detection in high-dimensional spaces

Novelty detection involves the construction of a “model of normality”, and then classifies test data as being either “normal” or “abnormal” with respect to that model. For this reason, it is often termed one-class classification. The approach is suitable for cases in which examples of “normal” behav...

詳細記述

書誌詳細
主要な著者: Clifton, D, Clifton, L, Hugueny, S, Tarassenko, L
フォーマット: Journal article
言語:English
出版事項: Springer US 2013

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