86 search results - page 9 / 18 » Bagging, Boosting, and C4.5 |
MCS
2000
Springer
13 years 11 months ago
2000
Springer
Ensemble methods are learning algorithms that construct a set of classi ers and then classify new data points by taking a (weighted) vote of their predictions. The original ensembl...
FLAIRS
2004
13 years 9 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...
ESANN
2006
13 years 9 months ago
2006
Abstract. Ensemble methods allow to improve the accuracy of classification methods. This work considers the application of one of these methods, named Rotation-based, when the clas...
JMLR
2010
13 years 2 months ago
2010
Massive Online Analysis (MOA) is a software environment for implementing algorithms and running experiments for online learning from evolving data streams. MOA is designed to deal...
ECAI
2008
Springer
13 years 9 months ago
2008
Springer
Many ensemble methods, such as Bagging, Boosting, Random Forest, etc, have been proposed and widely used in real world applications. Some of them are better than others on noisefre...