Open AccessVariable selection for correlated data in high dimension using decorrelation methods
Author(s) -
Émeline Perthame,
David Causeur,
ChingFan Sheu,
Chloé Friguet
Publication year - 2016
Publication title -
hal (le centre pour la communication scientifique directe)
Language(s) - English
Resource type - Conference proceedings
Subject(s) - feature selection , computer science , covariate , decorrelation , selection (genetic algorithm) , latent variable , independence (probability theory) , dimension (graph theory) , stability (learning theory) , machine learning , artificial intelligence , focus (optics) , variable (mathematics) , data mining , econometrics , statistics , mathematics , algorithm , mathematical analysis , pure mathematics , physics , optics
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