17 search results - page 4 / 4 » Explaining the Result of a Decision Tree to the End-User |
JMLR
2008
13 years 5 months ago
2008
Ensemble learning algorithms such as boosting can achieve better performance by averaging over the predictions of some base hypotheses. Nevertheless, most existing algorithms are ...
ESANN
2006
13 years 6 months ago
2006
Random Forests were introduced by Breiman for feature (variable) selection and improved predictions for decision tree models. The resulting model is often superior to AdaBoost and ...