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ESWA
2006
165views more  ESWA 2006»
13 years 5 months ago
Optimal ensemble construction via meta-evolutionary ensembles
In this paper we propose a meta-evolutionary approach to improve on the performance of individual classifiers. In the proposed system, individual classifiers evolve, competing to ...
YongSeog Kim, W. Nick Street, Filippo Menczer
ICTAI
2010
IEEE
13 years 3 months ago
Instance-Based Ensemble Pruning via Multi-Label Classification
Ensemble pruning is concerned with the reduction of the size of an ensemble prior to its combination. Its purpose is to reduce the space and time complexity of the ensemble and/or ...
Fotini Markatopoulou, Grigorios Tsoumakas, Ioannis...
KDD
2010
ACM
224views Data Mining» more  KDD 2010»
13 years 9 months ago
Ensemble pruning via individual contribution ordering
An ensemble is a set of learned models that make decisions collectively. Although an ensemble is usually more accurate than a single learner, existing ensemble methods often tend ...
Zhenyu Lu, Xindong Wu, Xingquan Zhu, Josh Bongard
ICML
2004
IEEE
14 years 5 months ago
Ensemble selection from libraries of models
We present a method for constructing ensembles from libraries of thousands of models. Model libraries are generated using different learning algorithms and parameter settings. For...
Rich Caruana, Alexandru Niculescu-Mizil, Geoff Cre...
ICDM
2007
IEEE
154views Data Mining» more  ICDM 2007»
13 years 9 months ago
Cocktail Ensemble for Regression
This paper is motivated to improve the performance of individual ensembles using a hybrid mechanism in the regression setting. Based on an error-ambiguity decomposition, we formal...
Yang Yu, Zhi-Hua Zhou, Kai Ming Ting