17 search results - page 1 / 4 » The Diversity of Regression Ensembles Combining Bagging and ... |
ICONIP
2008
13 years 6 months ago
2008
Abstract. The concept of Ensemble Learning has been shown to increase predictive power over single base learners. Given the bias-variancecovariance decomposition, diversity is char...
FLAIRS
2004
13 years 6 months ago
2004
In this work we present a novel approach to ensemble learning for regression models, by combining the ensemble generation technique of random subspace method with the ensemble int...
IDA
2007
Springer
13 years 11 months ago
2007
Springer
Random forests are one of the best performing methods for constructing ensembles. They derive their strength from two aspects: using random subsamples of the training data (as in b...
EVOW
2008
Springer
13 years 6 months ago
2008
Springer
Classifier fusion strategies have shown great potential to enhance the performance of pattern recognition systems. There is an agreement among researchers in classifier combination...
ICASSP
2008
IEEE
13 years 11 months ago
2008
IEEE
Bagging is an ensemble method that uses random resampling of a dataset to construct models. In classification scenarios, the random resampling procedure in bagging induces some c...