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...

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Bibliographic Details
Main Authors: Chen, S. (Author), Hong, X. (Author), Harris, C.J (Author)
Format: Article
Language:English
Published: 2004-08.
Subjects:
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