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» Feature subset selection bias for classification learning
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JMLR
2002
115views more  JMLR 2002»
14 years 9 months ago
PAC-Bayesian Generalisation Error Bounds for Gaussian Process Classification
Approximate Bayesian Gaussian process (GP) classification techniques are powerful nonparametric learning methods, similar in appearance and performance to support vector machines....
Matthias Seeger
SDM
2010
SIAM
218views Data Mining» more  SDM 2010»
14 years 11 months ago
Confidence-Based Feature Acquisition to Minimize Training and Test Costs
We present Confidence-based Feature Acquisition (CFA), a novel supervised learning method for acquiring missing feature values when there is missing data at both training and test...
Marie desJardins, James MacGlashan, Kiri L. Wagsta...
PKDD
2010
Springer
179views Data Mining» more  PKDD 2010»
14 years 7 months ago
Learning an Affine Transformation for Non-linear Dimensionality Reduction
The foremost nonlinear dimensionality reduction algorithms provide an embedding only for the given training data, with no straightforward extension for test points. This shortcomin...
Pooyan Khajehpour Tadavani, Ali Ghodsi
CVPR
2009
IEEE
16 years 4 months ago
Let the Kernel Figure it Out; Principled Learning of Pre-processing for Kernel Classifiers
Most modern computer vision systems for high-level tasks, such as image classification, object recognition and segmentation, are based on learning algorithms that are able to se...
Peter V. Gehler, Sebastian Nowozin
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BMCBI
2007
217views more  BMCBI 2007»
14 years 9 months ago
On consensus biomarker selection
Background: Recent development of mass spectrometry technology enabled the analysis of complex peptide mixtures. A lot of effort is currently devoted to the identification of biom...
Janusz Dutkowski, Anna Gambin