supervised learning. In addition, we investigate the effects of cost sensitive adaptations in CART and boosting and conclude that …

supervised learning. In addition, we investigate the effects of cost sensitive adaptations in CART and boosting and conclude that …

regression trees, bagging, random forest, boosting machines and neural networks. Finally, we provide methodologies for analysing …

supervised learning. In addition, we investigate the effects of cost sensitive adaptations in CART and boosting and conclude that …

In this paper various ensemble learning methods from machine learning and statistics are considered and applied to the … customer choice modeling problem. The application of ensemble learning usually improves the prediction quality of flexible … datasets using decision trees, ensemble versions of decision trees and the logistic regression model, which is a standard …

In this paper various ensemble learning methods from machine learning and statistics are considered and applied to the … customer choice modeling problem. The application of ensemble learning usually improves the prediction quality of flexible … datasets using decision trees, ensemble versions of decision trees and the logistic regression model, which is a standard …