A Meta-Learning Method to Select the Kernel Width in Support Vector Regression.

A Meta-Learning Method to Select the Kernel Width in Support Vector Regression.

The Support Vector Machine algorithm is sensitive to the choice of parameter settings. If these are not set correctly, the algorithm may have a substandard performance. Suggesting a good setting is thus an important problem. We propose a meta-learning methodology for this purpose and exploit informa...

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Bibliographic Details
Published in:Machine learning. 54, 3 (2004).
Main Author: Soares, Carlos
Format: Article
Language:English
Subjects:
Meta-learning.
Parameter setting.
Support vector machines.
Gaussian kernel.
Learning rankings.