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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| Published in: | Statistics and computing Vol. 33; no. 2 |
|---|---|
| Main Author: | |
| 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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