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COMSIS
2006
156views more  COMSIS 2006»
13 years 4 months ago
A Comparison of the Bagging and the Boosting Methods Using the Decision Trees Classifiers
In this paper we present an improvement of the precision of classification algorithm results. Two various approaches are known: bagging and boosting. This paper describes a set of ...
Kristína Machova, Miroslav Puszta, Frantise...
PAMI
2007
166views more  PAMI 2007»
13 years 4 months ago
A Comparison of Decision Tree Ensemble Creation Techniques
Abstract—We experimentally evaluate bagging and seven other randomizationbased approaches to creating an ensemble of decision tree classifiers. Statistical tests were performed o...
Robert E. Banfield, Lawrence O. Hall, Kevin W. Bow...
PAA
2002
13 years 4 months ago
Bagging, Boosting and the Random Subspace Method for Linear Classifiers
: Recently bagging, boosting and the random subspace method have become popular combining techniques for improving weak classifiers. These techniques are designed for, and usually ...
Marina Skurichina, Robert P. W. Duin
ECAI
2006
Springer
13 years 8 months ago
Ensembles of Grafted Trees
Grafted trees are trees that are constructed using two methods. The first method creates an initial tree, while the second method is used to complete the tree. In this work, the fi...
Juan José Rodríguez, Jesús Ma...
ICML
2006
IEEE
14 years 5 months ago
An empirical comparison of supervised learning algorithms
A number of supervised learning methods have been introduced in the last decade. Unfortunately, the last comprehensive empirical evaluation of supervised learning was the Statlog ...
Rich Caruana, Alexandru Niculescu-Mizil