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MCS
2007
Springer
14 years 2 months ago
An Experimental Study on Rotation Forest Ensembles
Rotation Forest is a recently proposed method for building classifier ensembles using independently trained decision trees. It was found to be more accurate than bagging, AdaBoost...
Ludmila I. Kuncheva, Juan José Rodrí...
BMCBI
2006
198views more  BMCBI 2006»
13 years 8 months ago
Gene selection and classification of microarray data using random forest
Background: Selection of relevant genes for sample classification is a common task in most gene expression studies, where researchers try to identify the smallest possible set of ...
Ramón Díaz-Uriarte, Sara Alvarez de ...
JMLR
2008
198views more  JMLR 2008»
13 years 7 months ago
Consistency of Random Forests and Other Averaging Classifiers
In the last years of his life, Leo Breiman promoted random forests for use in classification. He suggested using averaging as a means The second author's research was sponso...
Gérard Biau, Luc Devroye, Gábor Lugo...
APPROX
2007
Springer
115views Algorithms» more  APPROX 2007»
14 years 2 months ago
Improved Approximation Algorithms for the Spanning Star Forest Problem
A star graph is a tree of diameter at most two. A star forest is a graph that consists of node-disjoint star graphs. In the spanning star forest problem, given an unweighted graph ...
Ning Chen, Roee Engelberg, C. Thach Nguyen, Prasad...
MCS
2009
Springer
14 years 13 days ago
Random Ordinality Ensembles A Novel Ensemble Method for Multi-valued Categorical Data
Abstract. Data with multi-valued categorical attributes can cause major problems for decision trees. The high branching factor can lead to data fragmentation, where decisions have ...
Amir Ahmad, Gavin Brown