Search Results for author: Antonio Cuevas

Found 1 papers, 0 papers with code

The mRMR variable selection method: a comparative study for functional data

no code implementations13 Jul 2015 José R. Berrendero, Antonio Cuevas, José L. Torrecilla

The mRMR (minimum Redundance Maximum Relevance) procedure, proposed by Ding and Peng (2005) and Peng et al. (2005) is an algorithm to systematically perform variable selection, achieving a reasonable trade-off between relevance and redundancy.

Variable Selection

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