Objects of class boost_family define negative gradients of
loss functions to be optimized.
Objects can be created by calls of the form Family(...)
ngradient:a function with arguments y and f
implementing the negative gradient of
the loss function.
risk:a risk function with arguments y, f and w,
the weighted mean of the loss function by default.
offset:a function with argument y and w (weights)
for computing a scalar offset.
weights:a logical indicating if weights are allowed.
check_y:a function for checking the class / mode of a response variable.
nuisance:a function for extracting nuisance parameters.
response:inverse link function of a GLM or any other transformation on the scale of the response.
rclass:function to derive class predictions from conditional class probabilities (for models with factor response variable).
name:a character giving the name of the loss function for pretty printing.
charloss:a character, the deparsed loss function.
Family