Iterative feature selection in least square regression estimation

DOI10.1214/07-AIHP106zbMath1206.62067arXivmath/0511299OpenAlexW2095350026MaRDI QIDQ731450

Pierre Alquier

Publication date: 7 October 2009

Published in: Annales de l'Institut Henri Poincaré. Probabilités et Statistiques (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/math/0511299

zbMATH Keywords

support vector machinesconfidence regionsregression estimationstatistical learningthresholding methods

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Nonparametric tolerance and confidence regions (62G15) Learning and adaptive systems in artificial intelligence (68T05)

Related Items (4)

Fast learning rates in statistical inference through aggregation ⋮ Lasso, iterative feature selection and the correlation selector: oracle inequalities and numerical performances ⋮ Density estimation with quadratic loss: a confidence intervals method ⋮ Tight conditions for consistency of variable selection in the context of high dimensionality

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