Andrew Martin

Forest-type Regression with General Losses and Robust Forest

This paper introduces a new general framework for forest-type regression which allows the development of robust forest regressors by selecting from a large family of robust loss functions. In particular, when plugged in the squared error and quantile losses, it will recover the classical random fore…