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