In this paper, we present two ensemble learning algorithms which make use of boostrapping and out-of-bag estimation in an attempt to inherit the robustness of bagging to overfitti...
Ensemble learning aims to improve generalization ability by using multiple base learners. It is well-known that to construct a good ensemble, the base learners should be accurate a...
An ensemble is generated by training multiple component learners for a same task and then combining them for predictions. It is known that when lots of trained learners are availab...
This paper describes problem of prediction that is based on direct marketing data coming from Nationwide Products and Services Questionnaire (NPSQ) prepared by Polish division of A...
Jerzy Blaszczynski, Krzysztof Dembczynski, Wojciec...
While learning ensembles have been widely used for various pattern recognition tasks, surprisingly, they have found limited application in problems related to medical image analysi...
Anant Madabhushi, Jianbo Shi, Michael D. Feldman, ...