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» Data selection for support vector machine classifiers
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ECML
2004
Springer
15 years 3 months ago
Improving Random Forests
Random forests are one of the most successful ensemble methods which exhibits performance on the level of boosting and support vector machines. The method is fast, robust to noise,...
Marko Robnik-Sikonja
AMAI
2004
Springer
15 years 3 months ago
Biased Minimax Probability Machine for Medical Diagnosis
The Minimax Probability Machine (MPM) constructs a classifier, which provides a worst-case bound on the probability of misclassification of future data points based on reliable ...
Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. ...
CSB
2005
IEEE
141views Bioinformatics» more  CSB 2005»
15 years 3 months ago
Joint Genomic and Metabolomic Analysis of Toxic Dose-Response Experiments
A methodology has been implemented for analyzing microarray and NMR spectral data obtained from the same set of toxic-exposure dose-response experiments. The NMR spectra additiona...
Gary L. Jahns, Nicholas J. DelRaso, Mark P. Westri...
VISSYM
2003
14 years 11 months ago
Improving Topological Segmentation of Three-dimensional Vector Fields
We present three enhancements to accelerate the extraction of separatrices of three-dimensional vector fields, using intelligently selected “sample” streamlines. These enhanc...
Karim Mahrous, Janine Bennett, Bernd Hamann, Kenne...
BMCBI
2008
114views more  BMCBI 2008»
14 years 10 months ago
Identifying a few foot-and-mouth disease virus signature nucleotide strings for computational genotyping
Background: Serotypes of the Foot-and-Mouth disease viruses (FMDVs) were generally determined by biological experiments. The computational genotyping is not well studied even with...
Guohui Lin, Zhipeng Cai, Junfeng Wu, Xiu-Feng Wan,...