relative.influence {gbm} | R Documentation |
Helper functions for computing the relative influence of each variable in the gbm object.
relative.influence(object, n.trees) permutation.test.gbm(object, n.trees) gbm.loss(y,f,w,offset,dist,baseline)
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. |
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
.
Returns an unprocessed vector of estimated relative influences.
Greg Ridgeway gregr@rand.org
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.