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Published in:
2007 | OriginalPaper | Chapter
Two Bagging Algorithms with Coupled Learners to Encourage Diversity
Authors : Carlos Valle, Ricardo Ñanculef, Héctor Allende, Claudio Moraga
Published in: Advances in Intelligent Data Analysis VII
Publisher: Springer Berlin Heidelberg
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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 overfitting. As against bagging, with these algorithms learners have visibility on the other learners and cooperate to get diversity, a characteristic that has proved to be an issue of major concern to ensemble models. Experiments are provided using two regression problems obtained from UCI.