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» Feature selection for ranking using boosted trees
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BMCBI
2010
178views more  BMCBI 2010»
14 years 12 months ago
Selecting high-dimensional mixed graphical models using minimal AIC or BIC forests
Background: Chow and Liu showed that the maximum likelihood tree for multivariate discrete distributions may be found using a maximum weight spanning tree algorithm, for example K...
David Edwards, Gabriel C. G. de Abreu, Rodrigo Lab...
PR
2008
93views more  PR 2008»
14 years 11 months ago
Genetic algorithm-based feature set partitioning for classification problems
Feature set partitioning generalizes the task of feature selection by partitioning the feature set into subsets of features that are collectively useful, rather than by finding a ...
Lior Rokach
CANDC
2005
ACM
14 years 11 months ago
Gene selection from microarray data for cancer classification - a machine learning approach
A DNA microarray can track the expression levels of thousands of genes simultaneously. Previous research has demonstrated that this technology can be useful in the classification ...
Yu Wang 0008, Igor V. Tetko, Mark A. Hall, Eibe Fr...
BMCBI
2008
87views more  BMCBI 2008»
14 years 12 months ago
Identification of deleterious non-synonymous single nucleotide polymorphisms using sequence-derived information
Background: As the number of non-synonymous single nucleotide polymorphisms (nsSNPs), also known as single amino acid polymorphisms (SAPs), increases rapidly, computational method...
Jing Hu, Changhui Yan
SAMT
2009
Springer
176views Multimedia» more  SAMT 2009»
15 years 6 months ago
Shape-Based Autotagging of 3D Models for Retrieval
This paper describes an automatic annotation, or autotagging, algorithm that attaches textual tags to 3D models based on their shape and semantic classes. The proposed method emplo...
Ryutarou Ohbuchi, Shun Kawamura