De-noising boosting methods for variable selection and estimation subject to error-prone variables

Boosting is one of the most powerful statistical learning methods that combines multiple weak learners into a strong learner. The main idea of boosting is to sequentially apply the algorithm to enhance its performance. Recently, boosting methods have been implemented to handle variable selection. Ho...

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Bibliographic Details
Published in:Statistics and computing Vol. 33; no. 2
Main Author: Chen, Li-Pang
Format: Journal Article
Language:English
Published: New York Springer US 01.04.2023
Springer Nature B.V
Subjects:
ISSN:0960-3174, 1573-1375
Online Access:Get full text
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