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MCS
2010
Springer
14 years 2 months ago
"Good" and "Bad" Diversity in Majority Vote Ensembles
Although diversity in classifier ensembles is desirable, its relationship with the ensemble accuracy is not straightforward. Here we derive a decomposition of the majority vote er...
Gavin Brown, Ludmila I. Kuncheva
CEC
2007
IEEE
14 years 1 months ago
Evolutionary random neural ensembles based on negative correlation learning
— This paper proposes to incorporate bootstrap of data, random feature subspace and evolutionary algorithm with negative correlation learning to automatically design accurate and...
Huanhuan Chen, Xin Yao
CAEPIA
2003
Springer
14 years 18 days ago
Rotation-Based Ensembles
A new method for ensemble generation is presented. It is based on grouping the attributes in dierent subgroups, and to apply, for each group, an axis rotation, using Principal Com...
Juan José Rodríguez, Carlos J. Alons...
PAKDD
2004
ACM
143views Data Mining» more  PAKDD 2004»
14 years 21 days ago
Compact Dual Ensembles for Active Learning
Generic ensemble methods can achieve excellent learning performance, but are not good candidates for active learning because of their different design purposes. We investigate how...
Amit Mandvikar, Huan Liu, Hiroshi Motoda
ECAI
2008
Springer
13 years 9 months ago
Focused Ensemble Selection: A Diversity-Based Method for Greedy Ensemble Selection
Abstract. Ensemble selection deals with the reduction of an ensemble of predictive models in order to improve its efficiency and predictive performance. A number of ensemble select...
Ioannis Partalas, Grigorios Tsoumakas, Ioannis P. ...