KES-AMSTA 2011: Agent and Multi-Agent Systems: Technologies and Applications pp 495-503 | Cite as
Rotation Forest with GEP-Induced Expression Trees
Abstract
In this paper we propose integrating two techniques used in the field of the supervised machine learning. They include rotation forest and gene expression programming. The idea is to build a rotation forest based classifier ensembles using independently induced expression trees. To induce expression trees we apply gene expression programming. The paper includes an overview of the proposed approach. To evaluate the approach computational experiment has been carried out. Its results confirm high quality of the proposed ensemble classifiers integrating rotation forest with gene expression programming.
Keywords
gene expression programming rotation forest algorithm ensemble classifiersPreview
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