compboost (version 0.1.0)

LossBinomial: 0-1 Loss for binary classification derived of the binomial distribution

Description

This loss can be used for binary classification. The coding we have chosen here acts on \(y \in \{-1, 1\}\).

Format

S4 object.

Usage

LossBinomial$new()
LossBinomial$new(offset)

Arguments

offset [numeric(1)]

Numerical value which can be used to set a custom offset. If so, this value is returned instead of the loss optimal initialization.

Details

This class is a wrapper around the pure C++ implementation. To see the functionality of the C++ class visit https://schalkdaniel.github.io/compboost/cpp_man/html/classloss_1_1_binomial_loss.html.

Examples

# NOT RUN {
# Create new loss object:
bin.loss = LossBinomial$new()
bin.loss

# }