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MDAI
2005
Springer
13 years 11 months ago
Cancer Prediction Using Diversity-Based Ensemble Genetic Programming
Combining a set of classifiers has often been exploited to improve the classification performance. Accurate as well as diverse base classifiers are prerequisite to construct a good...
Jin-Hyuk Hong, Sung-Bae Cho
IJON
2008
116views more  IJON 2008»
13 years 5 months ago
Evolutionary ensemble of diverse artificial neural networks using speciation
Recently, many researchers have designed neural network architectures with evolutionary algorithms but most of them have used only the fittest solution of the last generation. To ...
Kyung-Joong Kim, Sung-Bae Cho
MCS
2010
Springer
13 years 7 months ago
Dynamic Selection of Ensembles of Classifiers Using Contextual Information
In a multiple classifier system, dynamic selection (DS) has been used successfully to choose only the best subset of classifiers to recognize the test samples. Dos Santos et al...
Paulo Rodrigo Cavalin, Robert Sabourin, Ching Y. S...
CBMS
2008
IEEE
13 years 7 months ago
Effectiveness of Local Feature Selection in Ensemble Learning for Prediction of Antimicrobial Resistance
In the real world concepts are often not stable but change over time. A typical example of this in the biomedical context is antibiotic resistance, where pathogen sensitivity may ...
Seppo Puuronen, Mykola Pechenizkiy, Alexey Tsymbal
GECCO
2006
Springer
171views Optimization» more  GECCO 2006»
13 years 9 months ago
Evolving ensemble of classifiers in random subspace
Various methods for ensemble selection and classifier combination have been designed to optimize the results of ensembles of classifiers. Genetic algorithm (GA) which uses the div...
Albert Hung-Ren Ko, Robert Sabourin, Alceu de Souz...