Principal Component Analysis: A Generalized Gini Approach - Archive ouverte HAL Accéder directement au contenu
Pré-Publication, Document De Travail Année : 2019

Principal Component Analysis: A Generalized Gini Approach

Résumé

A principal component analysis based on the generalized Gini correlation index is proposed (Gini PCA). The Gini PCA generalizes the standard PCA based on the variance. It is shown, in the Gaussian case, that the standard PCA is equivalent to the Gini PCA. It is also proven that the dimensionality reduction based on the generalized Gini correlation matrix, that relies on city-block distances, is robust to out-liers. Monte Carlo simulations and an application on cars data (with outliers) show the robustness of the Gini PCA and provide different interpretations of the results compared with the variance PCA.
Fichier principal
Vignette du fichier
GINI.pdf (1.27 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-02327521 , version 1 (22-10-2019)

Identifiants

  • HAL Id : hal-02327521 , version 1

Citer

Arthur Charpentier, Stéphane Mussard, Tea Ouraga. Principal Component Analysis: A Generalized Gini Approach. 2019. ⟨hal-02327521⟩
98 Consultations
233 Téléchargements

Partager

Gmail Facebook X LinkedIn More