447 search results - page 31 / 90 » Choosing Multiple Parameters for Support Vector Machines |
ICML
2009
IEEE
15 years 10 months ago
2009
IEEE
We present a general Bayesian framework for hyperparameter tuning in L2-regularized supervised learning models. Paradoxically, our algorithm works by first analytically integratin...
ICPR
2004
IEEE
15 years 11 months ago
2004
IEEE
This paper describes the training of classifiers entirely based on virtual images, rendered by a ray-tracing software. Two classifiers, a support vector machine and a polynomial c...
ICPR
2008
IEEE
15 years 4 months ago
2008
IEEE
Support Vector Machines (SVMs), though accurate, are still difficult to solve large-scale applications, due to the computational and storage requirement. To relieve this problem,...
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ICANN
2005
Springer
15 years 3 months ago
2005
Springer
Abstract. Tuning hyper-parameters is a necessary step to improve learning algorithm performances. For Support Vector Machine classifiers, adjusting kernel parameters increases dra...
JMLR
2010
14 years 4 months ago
2010
Simple features constructed from order book data for the EURUSD currency pair were used to construct a set of kernels. These kernels were used both individually and simultaneously...