37 search results - page 2 / 8 » Using Evolutionary Multiobjective Techniques for Imbalanced ... |
ICPR
2010
IEEE
13 years 7 months ago
2010
IEEE
Appropriate feature selection is a very crucial issue in any machine learning framework, specially in Maximum Entropy (ME). In this paper, the selection of appropriate features for...
GECCO
2003
Springer
13 years 10 months ago
2003
Springer
One advantage of evolutionary multiobjective optimization (EMO) algorithms over classical approaches is that many non-dominated solutions can be simultaneously obtained by their si...
GECCO
2007
Springer
13 years 11 months ago
2007
Springer
The main motivation for using a multi–objective evolutionary algorithm for finding biclusters in gene expression data is motivated by the fact that when looking for biclusters ...
GECCO
2006
Springer
13 years 8 months ago
2006
Springer
Semi-supervised classification uses aspects of both unsupervised and supervised learning to improve upon the performance of traditional classification methods. Semi-supervised clu...
TNN
2010
12 years 11 months ago
2010
In this paper, we present the evolution of adaptive resonance theory (ART) neural network architectures (classifiers) using a multiobjective optimization approach. In particular, w...