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» A Comparison of Decision Tree Ensemble Creation Techniques
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IBPRIA
2007
Springer
13 years 11 months ago
Random Forest for Gene Expression Based Cancer Classification: Overlooked Issues
Random forest is a collection (ensemble) of decision trees. It is a popular ensemble technique in pattern recognition. In this article, we apply random forest for cancer classifica...
Oleg Okun, Helen Priisalu
CVPR
2005
IEEE
14 years 9 months ago
Random Subspaces and Subsampling for 2-D Face Recognition
Random subspaces are a popular ensemble construction technique that improves the accuracy of weak classifiers. It has been shown, in different domains, that random subspaces combi...
Nitesh V. Chawla, Kevin W. Bowyer
LATA
2009
Springer
14 years 2 months ago
Rigid Tree Automata
We introduce the class of Rigid Tree Automata (RTA), an extension of standard bottom-up automata on ranked trees with distinguished states called rigid. Rigid states define a rest...
Florent Jacquemard, Francis Klay, Camille Vacher
FSS
2008
69views more  FSS 2008»
13 years 7 months ago
A methodology for automated fuzzy model generation
In this paper we propose a generic methodology for the automated generation of fuzzy models. The methodology is realized in three stages. Initially, a crisp model is created and i...
Markos G. Tsipouras, Themis P. Exarchos, Dimitrios...
BMCBI
2008
169views more  BMCBI 2008»
13 years 7 months ago
A comprehensive comparison of random forests and support vector machines for microarray-based cancer classification
Background: Cancer diagnosis and clinical outcome prediction are among the most important emerging applications of gene expression microarray technology with several molecular sig...
Alexander R. Statnikov, Lily Wang, Constantin F. A...