416 search results - page 33 / 84 » Nonlinear Feature Selection by Relevance Feature Vector Mach... |
COLT
1999
Springer
14 years 15 hour ago
1999
Springer
—Support vector (SV) machines are linear classifiers that use the maximum margin hyperplane in a feature space defined by a kernel function. Until recently, the only bounds on th...
ICNC
2005
Springer
14 years 1 months ago
2005
Springer
The Support vector machines derive the class decision hyper planes from a few, selected prototypes, the support vectors (SVs) according to the principle of structure risk minimizat...
PKDD
2009
Springer
14 years 2 months ago
2009
Springer
Most accurate predictions are typically obtained by learning machines with complex feature spaces (as e.g. induced by kernels). Unfortunately, such decision rules are hardly access...
ICIAP
1999
ACM
14 years 3 hour ago
1999
ACM
—Texture features that are based on the local power spectrum obtained by a bank of Gabor filters are compared. The features differ in the type of nonlinear post-processing which ...
GECCO
2008
Springer
13 years 8 months ago
2008
Springer
In this paper, we show that a Bio-inspired classifier’s accuracy can be dramatically improved if it operates on intelligent features. We propose a novel set of intelligent feat...