447 search results - page 31 / 90 » Choosing Multiple Parameters for Support Vector Machines |
ICML
2009
IEEE
14 years 8 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
14 years 9 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
14 years 2 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,...
ICANN
2005
Springer
14 years 1 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
13 years 2 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...