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A Multivariate Extreme Value Theory Approach to Anomaly Clustering and Visualization

Archive ouverte | Chiapino, Maël | CCSD

International audience. In a wide variety of situations, anomalies in the behaviour of a complex system, whose health is monitored through the observation of a random vector X = (X1,. .. , X d) valued in R d , corre...

One Class Splitting Criteria for Random Forests

Archive ouverte | Goix, Nicolas | CCSD

Random Forests (RFs) are strong machine learning tools for classification and regression. However, they remain supervised algorithms, and no extension of RFs to the one-class setting has been proposed, except for techniques based ...

Discovering patterns in high-dimensional extremes. Apprentissage de structures dans les valeurs extrêmes en grande dimension

Archive ouverte | Chiapino, Maël | CCSD

We present and study unsupervised learning methods of multivariate extreme phenomena in high-dimension. Considering a random vector on which each marginal is heavy-tailed, the study of its behavior in extreme regions is no longer ...

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