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» Predicting relative performance of classifiers from samples
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ICIAR
2005
Springer
14 years 1 months ago
Multi-dimensional Color Histograms for Segmentation of Wounds in Images
The work investigates the use of multi dimensional histograms for segmentation of images of chronic wounds. We employ a Support Vector Machine (SVM) classifier for automatic extrac...
Marina Kolesnik, Ales Fexa
CVPR
2008
IEEE
14 years 9 months ago
Margin-based discriminant dimensionality reduction for visual recognition
Nearest neighbour classifiers and related kernel methods often perform poorly in high dimensional problems because it is infeasible to include enough training samples to cover the...
Hakan Cevikalp, Bill Triggs, Frédéri...
EOR
2007
85views more  EOR 2007»
13 years 7 months ago
Reject inference, augmentation, and sample selection
Many researchers see the need for reject inference in credit scoring models to come from a sample selection problem whereby a missing variable results in omitted variable bias. Al...
John Banasik, Jonathan Crook
BMCBI
2010
97views more  BMCBI 2010»
13 years 7 months ago
Biomarker discovery in heterogeneous tissue samples -taking the in-silico deconfounding approach
Background: For heterogeneous tissues, such as blood, measurements of gene expression are confounded by relative proportions of cell types involved. Conclusions have to rely on es...
Dirk Repsilber, Sabine Kern, Anna Telaar, Gerhard ...
AIME
1997
Springer
13 years 11 months ago
Detecting Very Early Stages of Dementia from Normal Aging with Machine Learning Methods
We used Machine Learning (ML) methods to learn the best decision rules to distinguish normal brain aging from the earliest stages of dementia using subsamples of 198 normal and 244...
William Rodman Shankle, Subramani Mani, Michael J....