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COMSIS
2006
156views more  COMSIS 2006»
14 years 12 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...
ILP
2005
Springer
15 years 5 months ago
Predicate Selection for Structural Decision Trees
Abstract. We study predicate selection functions (also known as splitting rules) for structural decision trees and propose two improvements to existing schemes. The first is in cl...
Kee Siong Ng, John W. Lloyd
FLAIRS
2001
15 years 1 months ago
Hybrid Decision Tree Learners with Alternative Leaf Classifiers: An Empirical Study
Therehasbeensurprisinglylittle researchso far that systematicallyinvestigatedthe possibilityof constructinghybrid learningalgorithmsbysimplelocal modificationsto decision tree lea...
Alexander K. Seewald, Johann Petrak, Gerhard Widme...
ICML
2003
IEEE
16 years 20 days ago
Learning with Positive and Unlabeled Examples Using Weighted Logistic Regression
The problem of learning with positive and unlabeled examples arises frequently in retrieval applications. We transform the problem into a problem of learning with noise by labelin...
Wee Sun Lee, Bing Liu