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AI
2002
Springer
14 years 9 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
BMCBI
2004
133views more  BMCBI 2004»
14 years 9 months ago
Artificial neural network approach for selection of susceptible single nucleotide polymorphisms and construction of prediction m
Background: Screening of various gene markers such as single nucleotide polymorphism (SNP) and correlation between these markers and development of multifactorial disease have pre...
Yasuyuki Tomita, Shuta Tomida, Yuko Hasegawa, Yoic...
IJCNN
2007
IEEE
15 years 3 months ago
A Wrapper for Projection Pursuit Learning
– Constructive algorithms are effective methods for designing Artificial Neural Networks (ANN) with good accuracy and generalization capability, yet with parsimonious network str...
Leonardo M. Holschuh, Clodoaldo Ap. M. Lima, Ferna...
ESANN
2000
14 years 11 months ago
A statistical model selection strategy applied to neural networks
In statistical modelling, an investigator must often choose a suitable model among a collection of viable candidates. There is no consensus in the research community on how such a...
Joaquín Pizarro Junquera, Elisa Guerrero V&...
IJCNN
2000
IEEE
15 years 1 months ago
A Training Method with Small Computation for Classification
A training data selection method for multi-class data is proposed. This method can be used for multilayer neural networks (MLNN). The MLNN can be applied to pattern classification...
Kazuyuki Hara, Kenji Nakayama