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JMLR
2008
198views more  JMLR 2008»
9 years 5 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...
PAMI
1998
127views more  PAMI 1998»
9 years 5 months ago
The Random Subspace Method for Constructing Decision Forests
—Much of previous attention on decision trees focuses on the splitting criteria and optimization of tree sizes. The dilemma between overfitting and achieving maximum accuracy is ...
Tin Kam Ho
TIT
2016
29views Education» more  TIT 2016»
4 years 1 months ago
Random Forests and Kernel Methods
—Random forests are ensemble methods which grow trees as base learners and combine their predictions by averaging. Random forests are known for their good practical performance, ...
Erwan Scornet
BMCBI
2010
150views more  BMCBI 2010»
9 years 5 months ago
Automatic structure classification of small proteins using random forest
Background: Random forest, an ensemble based supervised machine learning algorithm, is used to predict the SCOP structural classification for a target structure, based on the simi...
Pooja Jain, Jonathan D. Hirst
BMCBI
2008
169views more  BMCBI 2008»
9 years 5 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...
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