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BMCBI
2008
186views more  BMCBI 2008»
13 years 9 months ago
Variable selection for large p small n regression models with incomplete data: Mapping QTL with epistases
Background: Identifying quantitative trait loci (QTL) for both additive and epistatic effects raises the statistical issue of selecting variables from a large number of candidates...
Min Zhang, Dabao Zhang, Martin T. Wells
BMCBI
2010
151views more  BMCBI 2010»
13 years 9 months ago
Classification of G-protein coupled receptors based on support vector machine with maximum relevance minimum redundancy and gene
Background: Because a priori knowledge about function of G protein-coupled receptors (GPCRs) can provide useful information to pharmaceutical research, the determination of their ...
Zhanchao Li, Xuan Zhou, Zong Dai, Xiaoyong Zou
SDM
2009
SIAM
175views Data Mining» more  SDM 2009»
14 years 6 months ago
Low-Entropy Set Selection.
Most pattern discovery algorithms easily generate very large numbers of patterns, making the results impossible to understand and hard to use. Recently, the problem of instead sel...
Hannes Heikinheimo, Jilles Vreeken, Arno Siebes, H...
ESANN
2000
13 years 10 months ago
Confidence estimation methods for neural networks : a practical comparison
Feed-forward neural networks (Multi-Layered Perceptrons) are used widely in real-world regression or classification tasks. A reliable and practical measure of prediction "conf...
Georgios Papadopoulos, Peter J. Edwards, Alan F. M...
CORR
2002
Springer
126views Education» more  CORR 2002»
13 years 8 months ago
Unsupervised Discovery of Morphemes
We present two methods for unsupervised segmentation of words into morphemelike units. The model utilized is especially suited for languages with a rich morphology, such as Finnis...
Mathias Creutz, Krista Lagus