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ADBIS
2003
Springer
108views Database» more  ADBIS 2003»
14 years 23 days ago
Dynamic Integration of Classifiers in the Space of Principal Components
Recent research has shown the integration of multiple classifiers to be one of the most important directions in machine learning and data mining. It was shown that, for an ensemble...
Alexey Tsymbal, Mykola Pechenizkiy, Seppo Puuronen...
JCST
2006
97views more  JCST 2006»
13 years 7 months ago
Image Region Selection and Ensemble for Face Recognition
In this paper, a novel framework for face recognition, namely Selective Ensemble of Image Regions (SEIR), is proposed. In this framework, all possible regions in the face image are...
Xin Geng, Zhi-Hua Zhou
FSKD
2006
Springer
122views Fuzzy Logic» more  FSKD 2006»
13 years 11 months ago
Context Modeling with Bayesian Network Ensemble for Recognizing Objects in Uncertain Environments
Abstract. It is difficult to understand a scene from visual information in uncertain real world. Since Bayesian network (BN) is known as good in this uncertainty, it has received s...
Seung-Bin Im, Youn-Suk Song, Sung-Bae Cho
CEC
2009
IEEE
13 years 11 months ago
Using genetic programming to obtain implicit diversity
—When performing predictive data mining, the use of ensembles is known to increase prediction accuracy, compared to single models. To obtain this higher accuracy, ensembles shoul...
Ulf Johansson, Cecilia Sönströd, Tuve L&...
AAAI
2008
13 years 10 months ago
Constraint Projections for Ensemble Learning
It is well-known that diversity among base classifiers is crucial for constructing a strong ensemble. Most existing ensemble methods obtain diverse individual learners through res...
Daoqiang Zhang, Songcan Chen, Zhi-Hua Zhou, Qiang ...