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...
| Main Authors: | , , , |
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| Formato: | Journal article |
| Idioma: | English |
| Publicado em: |
Springer US
2013
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