gfboost (version 0.1.1)

LocRank: Localized ranking familty

Description

Gradient-free Gradient Boosting family for the localized ranking loss function including its fast computation.

Usage

LocRank(K)

Arguments

K

Indicates that we are interesting in the top \(K\) instances and their correct ordering. Must be an integer between 1 and the number \(n\) of observations.

Value

A Boosting family object

Details

The localized ranking loss combines the hard and the weak ranking loss, i.e., it penalizes misrankings at the top of the list (the best \(K\) instances according to the response value) and ''misclassification'' in the sense that instances belonging to the top of the list are ranked lower and vice versa. The localized ranking loss already returns a normalized loss that can take values between 0 and 1. LocRank returns a family object as in the package mboost.

References

Werner, T., Gradient-Free Gradient Boosting, PhD Thesis, Carl von Ossietzky University Oldenburg, 2020, Equation (5.2.5)

T. Hothorn, P. B<U+00FC>hlmann, T. Kneib, M. Schmid, and B. Hofner. mboost: Model-Based Boosting, 2017

Examples

# NOT RUN {
{y<-c(-3, 10.3,-8, 12, 14,-0.5, 29,-1.1,-5.7, 119)
 yhat<-c(0.02, 0.6, 0.1, 0.47, 0.82, 0.04, 0.77, 0.09, 0.01, 0.79)
 LocRank(4)@risk(y,yhat)}
{y<-c(-3, 10.3,-8, 12, 14,-0.5, 29,-1.1,-5.7, 119)
 yhat<-c(0.02, 0.6, 0.1, 0.47, 0.82, 0.04, 0.77, 0.09, 0.01, 0.79)
 LocRank(5)@risk(y,yhat)}
# }