Sciweavers

76 search results - page 8 / 16
» Least squares linear discriminant analysis
Sort
View
ARTMED
2007
347views more  ARTMED 2007»
13 years 7 months ago
A combined MRI and MRSI based multiclass system for brain tumour recognition using LS-SVMs with class probabilities and feature
Objective: This study investigates the use of automated pattern recognition methods on magnetic resonance data with the ultimate goal to assist clinicians in the diagnosis of brai...
Jan Luts, Arend Heerschap, Johan A. K. Suykens, Sa...
BIOINFORMATICS
2005
109views more  BIOINFORMATICS 2005»
13 years 7 months ago
Prediction error estimation: a comparison of resampling methods
In genomic studies, thousands of features are collected on relatively few samples. One of the goals of these studies is to build classifiers to predict the outcome of future obser...
Annette M. Molinaro, Richard Simon, Ruth M. Pfeiff...
ADAC
2008
193views more  ADAC 2008»
13 years 7 months ago
A constrained-optimization based half-quadratic algorithm for robustly fitting sets of linearly parametrized curves
We consider the problem of multiple fitting of linearly parametrized curves, that arises in many computer vision problems such as road scene analysis. Data extracted from images us...
Jean-Philippe Tarel, Sio-Song Ieng, Pierre Charbon...
BMCBI
2008
172views more  BMCBI 2008»
13 years 7 months ago
Classification of drug molecules considering their IC50 values using mixed-integer linear programming based hyper-boxes method
Background: A priori analysis of the activity of drugs on the target protein by computational approaches can be useful in narrowing down drug candidates for further experimental t...
Pelin Armutlu, Muhittin Emre Ozdemir, Fadime Ü...
PRL
2006
98views more  PRL 2006»
13 years 7 months ago
Data complexity assessment in undersampled classification of high-dimensional biomedical data
Regularized linear classifiers have been successfully applied in undersampled, i.e. small sample size/high dimensionality biomedical classification problems. Additionally, a desig...
Richard Baumgartner, Ray L. Somorjai