Sparse modelling using orthogonal forward regression with PRESS statistic and regularization
The paper introduces an efficient construction algorithm for obtaining sparse linear-in-the-weights regression models based on an approach of directly optimizing model generalization capability. This is achieved by utilizing the delete-1 cross validation concept and the associated leave-one-out test...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
2004-04.
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| Subjects: | |
| Online Access: | Get fulltext Get fulltext |