Statistique et Big Data Analytics; Volumétrie, L'Attaque des Clones

Philippe Besse (1) , Nathalie Vialaneix (2)

1 IMT - Institut de Mathématiques de Toulouse UMR5219
2 MIAT INRA - Unité de Mathématiques et Informatique Appliquées de Toulouse

This article assumes acquired the skills and expertise of a statistician in unsupervised (NMF, k-means, SVD) and supervised learning (regression, CART, random forest). What skills and knowledge do a statistician must acquire to reach the "Volume" scale of big data? After a quick overview of the different strategies available and especially of those imposed by Hadoop, the algorithms of some available learning methods are outlined in order to understand how they are adapted to the strong stresses of the Map-Reduce functionalities

Mots clés: Statistique; Fouille de Données; Grande Dimension; Apprentissage Statistique; Méga Données; algorithmes; Hadoop; Map-Reduce; Scalability.; Scalability

Domaines: Statistiques [math.ST]; Théorie [stat.TH]; Apprentissage [cs.LG]

Philippe Besse, Nathalie Vialaneix. Statistique et Big Data Analytics; Volumétrie, L'Attaque des Clones. 2014. ⟨hal-00995801v3⟩