Forest Representation Learning Guided by Margin Distribution

7 May 2019Shen-Huan LvLiang YangZhi-Hua Zhou

In this paper, we reformulate the forest representation learning approach as an additive model which boosts the augmented feature instead of the prediction. We substantially improve the upper bound of generalization gap from $\mathcal{O}(\sqrt\frac{\ln m}{m})$ to $\mathcal{O}(\frac{\ln m}{m})$, while $\lambda$ - the margin ratio between the margin standard deviation and the margin mean is small enough... (read more)

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