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ACML
2009
Springer
15 years 7 months ago
Improving Adaptive Bagging Methods for Evolving Data Streams
We propose two new improvements for bagging methods on evolving data streams. Recently, two new variants of Bagging were proposed: ADWIN Bagging and Adaptive-Size Hoeffding Tree (...
Albert Bifet, Geoffrey Holmes, Bernhard Pfahringer...
BMCBI
2010
224views more  BMCBI 2010»
15 years 2 months ago
An adaptive optimal ensemble classifier via bagging and rank aggregation with applications to high dimensional data
Background: Generally speaking, different classifiers tend to work well for certain types of data and conversely, it is usually not known a priori which algorithm will be optimal ...
Susmita Datta, Vasyl Pihur, Somnath Datta
128
Voted
ICML
2003
IEEE
16 years 3 months ago
Boosting Lazy Decision Trees
This paper explores the problem of how to construct lazy decision tree ensembles. We present and empirically evaluate a relevancebased boosting-style algorithm that builds a lazy ...
Xiaoli Zhang Fern, Carla E. Brodley
TSMC
2008
132views more  TSMC 2008»
15 years 2 months ago
Ensemble Algorithms in Reinforcement Learning
This paper describes several ensemble methods that combine multiple different reinforcement learning (RL) algorithms in a single agent. The aim is to enhance learning speed and fin...
Marco A. Wiering, Hado van Hasselt
IJON
2010
148views more  IJON 2010»
15 years 22 days ago
Modeling radiation-induced lung injury risk with an ensemble of support vector machines
Radiation-induced lung injury, radiation pneumonitis (RP), is a potentially fatal side-effect of thoracic radiation therapy. In this work, using an ensemble of support vector mac...
Todd W. Schiller, Yixin Chen, Issam El-Naqa, Josep...