Sparse kernel density construction using orthogonal forward regression with leave-one-out test score and local regularization
The paper presents an efficient construction algorithm for obtaining sparse kernel density estimates based on a regression approach that directly optimizes model generalization capability. Computational efficiency of the density construction is ensured using an orthogonal forward regression, and the...
Main Authors: | , , |
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Format: | Article |
Language: | English |
Published: |
2004-08.
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Subjects: | |
Online Access: | Get fulltext Get fulltext |