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ICPR
2008
IEEE
13 years 11 months ago
Improving Gaussian processes classification by spectral data reorganizing
We improve Gaussian processes (GP) classification by reorganizing the (non-stationary and anisotropic) data to better fit to the isotropic GP kernel. First, the data is partitione...
Hang Zhou, David Suter
BMCBI
2010
158views more  BMCBI 2010»
13 years 4 months ago
A Bayesian network approach to feature selection in mass spectrometry data
Background: Time-of-flight mass spectrometry (TOF-MS) has the potential to provide non-invasive, high-throughput screening for cancers and other serious diseases via detection of ...
Karl W. Kuschner, Dariya I. Malyarenko, William E....
ICDM
2007
IEEE
129views Data Mining» more  ICDM 2007»
13 years 6 months ago
Feature Selection for Nonlinear Kernel Support Vector Machines
An easily implementable mixed-integer algorithm is proposed that generates a nonlinear kernel support vector machine (SVM) classifier with reduced input space features. A single ...
Olvi L. Mangasarian, Gang Kou
PKDD
2009
Springer
152views Data Mining» more  PKDD 2009»
13 years 11 months ago
Feature Selection for Value Function Approximation Using Bayesian Model Selection
Abstract. Feature selection in reinforcement learning (RL), i.e. choosing basis functions such that useful approximations of the unkown value function can be obtained, is one of th...
Tobias Jung, Peter Stone
PKDD
2009
Springer
113views Data Mining» more  PKDD 2009»
13 years 11 months ago
Feature Selection for Density Level-Sets
A frequent problem in density level-set estimation is the choice of the right features that give rise to compact and concise representations of the observed data. We present an e...
Marius Kloft, Shinichi Nakajima, Ulf Brefeld