Building Diversified Multiple Trees for Classification in High Dimensional Noisy Biomedical Data

18 Dec 2016Jiuyong LiLin LiuJixue LiuRyan Green

It is common that a trained classification model is applied to the operating data that is deviated from the training data because of noise. This paper demonstrates that an ensemble classifier, Diversified Multiple Tree (DMT), is more robust in classifying noisy data than other widely used ensemble methods... (read more)

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