This loss can be used for regression with $$y \in \mathrm{R}$$.

Format

S4 object.

Details

Loss Function: $$L(y, f(x)) = h| y - f(x)|$$ Gradient: $$\frac{\delta}{\delta f(x)}\ L(y, f(x)) = -h\mathrm{sign}( y - f(x))$$ Initialization: $$\hat{f}^{[0]}(x) = \mathrm{arg~min}_{c\in R}\ \frac{1}{n}\sum\limits_{i=1}^n L(y^{(i)}, c) = \mathrm{quantile}(y, q)$$

Usage

LossAbsolute$new() LossAbsolute$new(quantile)