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» Genetic Algorithm based Selective Neural Network Ensemble
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CIDM
2009
IEEE
13 years 11 months ago
Ensemble member selection using multi-objective optimization
— Both theory and a wealth of empirical studies have established that ensembles are more accurate than single predictive models. Unfortunately, the problem of how to maximize ens...
Tuve Löfström, Ulf Johansson, Henrik Bos...
GECCO
2004
Springer
166views Optimization» more  GECCO 2004»
13 years 10 months ago
Evolutionary Ensemble for Stock Prediction
We propose a genetic ensemble of recurrent neural networks for stock prediction model. The genetic algorithm tunes neural networks in a two-dimensional and parallel framework. The ...
Yung-Keun Kwon, Byung Ro Moon
ESWA
2006
165views more  ESWA 2006»
13 years 4 months ago
Optimal ensemble construction via meta-evolutionary ensembles
In this paper we propose a meta-evolutionary approach to improve on the performance of individual classifiers. In the proposed system, individual classifiers evolve, competing to ...
YongSeog Kim, W. Nick Street, Filippo Menczer
GECCO
2005
Springer
153views Optimization» more  GECCO 2005»
13 years 10 months ago
Evolving neural network ensembles for control problems
In neuroevolution, a genetic algorithm is used to evolve a neural network to perform a particular task. The standard approach is to evolve a population over a number of generation...
David Pardoe, Michael S. Ryoo, Risto Miikkulainen
FLAIRS
2006
13 years 6 months ago
Introducing GEMS - A Novel Technique for Ensemble Creation
The main contribution of this paper is to suggest a novel technique for automatic creation of accurate ensembles. The technique proposed, named GEMS, first trains a large number o...
Ulf Johansson, Tuve Löfström, Rikard K&o...