gbm (version 1.2)

relative.influence: Methods for estimating relative influence

Description

Helper functions for computing the relative influence of each variable in the gbm object.

Usage

relative.influence <- function(object, n.trees)
permutation.test.gbm <- function(object, n.trees)
gbm.loss <- function(y,f,w,offset,dist,baseline)

Arguments

object

a gbm object created from an initial call to gbm.

n.trees

the number of trees to use for computations.

y,f,w,offset,dist,baseline

For gbm.loss: These components are the outcome, predicted value, observation weight, offset, distribution, and comparison loss function, respectively.

Value

• Returns an unprocessed vector of estimated relative influences.

Details

This is not intended for end-user use. These functions offer the different methods for computing the relative influence in summary.gbm. gbm.loss is a helper function for permutation.test.gbm.

References

J.H. Friedman (2001). "Greedy Function Approximation: A Gradient Boosting Machine," Annals of Statistics 29(5):1189-1232.

L. Breiman (2001). "Random Forests," Available at ftp://ftp.stat.berkeley.edu/pub/users/breiman/randomforest2001.pdf.

See Also

summary.gbm