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ICANN
2010
Springer
14 years 9 months ago
Using Evolutionary Multiobjective Techniques for Imbalanced Classification Data
The aim of this paper is to study the use of Evolutionary Multiobjective Techniques to improve the performance of Neural Networks (NN). In particular, we will focus on classificati...
Sandra García, Ricardo Aler, Inés Ma...
GECCO
2008
Springer
118views Optimization» more  GECCO 2008»
15 years 28 days ago
Unsupervised learning of echo state networks: balancing the double pole
A possible alternative to fine topology tuning for Neural Network (NN) optimization is to use Echo State Networks (ESNs), recurrent NNs built upon a large reservoir of sparsely r...
Fei Jiang, Hugues Berry, Marc Schoenauer
ICANN
2005
Springer
15 years 5 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
ESANN
2004
15 years 1 months ago
Neural methods for non-standard data
Standard pattern recognition provides effective and noise-tolerant tools for machine learning tasks; however, most approaches only deal with real vectors of a finite and fixed dime...
Barbara Hammer, Brijnesh J. Jain
ASC
2006
15 years 1 months ago
Simulation-based optimisation using local search and neural network metamodels
This paper presents a new algorithm for enhancing the efficiency of simulation-based optimisation using local search and neural network metamodels. The local search strategy is ba...
Anna Persson, Henrik Grimm, Amos Ng