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AI
2002
Springer
13 years 8 months ago
Ensembling neural networks: Many could be better than all
Neural network ensemble is a learning paradigm where many neural networks are jointly used to solve a problem. In this paper, the relationship between the ensemble and its compone...
Zhi-Hua Zhou, Jianxin Wu, Wei Tang
ICANN
2003
Springer
14 years 1 months ago
Neural Network Ensemble with Negatively Correlated Features for Cancer Classification
The development of microarray technology has supplied a large volume of data to many fields. In particular, it has been applied to prediction and diagnosis of cancer, so that it ex...
Hong-Hee Won, Sung-Bae Cho
IJON
2008
109views more  IJON 2008»
13 years 8 months ago
Unsupervised learning neural network with convex constraint: Structure and algorithm
This paper proposed a kind of unsupervised learning neural network model, which has special structure and can realize an evaluation and classification of many groups by the compres...
Hengqing Tong, Tianzhen Liu, Qiaoling Tong
ICANN
2005
Springer
14 years 2 months ago
Neural Network Classifers in Arrears Management
Abstract. The literature suggests that an ensemble of classifiers outperforms a single classifier across a range of classification problems. This paper investigates the applicat...
Esther Scheurmann, Chris Matthews
ICPR
2002
IEEE
14 years 9 months ago
Learning and Extracting Edges from Images by a Modified Hopfield Neural Network
This paper introduced a modified unsupervised Hopfield network that can learn the underlying process in an edge detection task from grey level images. After the learning phase, th...
Sylvain Chartier, Richard Lepage