plot.error {randomSurvivalForest} | R Documentation |
Plot out-of-bag (OOB) error rate for the ensemble as a function of number of trees in the forest. Also plots importance values for predictors. Note that this is the default plot method for the package.
plot.error(x, ...) plot.rsf(x, ...)
x |
An object of class (rsf, grow) or (rsf,
predict) . |
... |
Further arguments passed to or from other methods. |
Plot of OOB error rate for the ensemble, with the b-th value being the error rate for the ensemble formed using the first b trees. Error rate is 1-C, where C is Harrell's concordance index. Rates given are between 0 and 1, with 0.5 representing the benchmark value of a procedure based on random guessing. A value of 0 is perfect.
If importance
=TRUE used in original rsf
call (the
default setting), importance values for predictors will be included in
the object x
. In this case, plot.error
will plot, as
well as print, these values. The vector predictorWt
is also
printed as a side effect.
Hemant Ishwaran hemant.ishwaran@gmail.com and Udaya B. Kogalur ubk2101@columbia.edu
H. Ishwaran and Udaya B. Kogalur (2006). Random Survival Forests. Cleveland Clinic Technical Report.
L. Breiman (2001). Random forests, Machine Learning, 45:5-32.
F.E. Harrell et al. (1982). Evaluating the yield of medical tests, J. Amer. Med. Assoc., 247, 2543-2546.
rsf
,
predict.rsf
.
data(veteran, package = "randomSurvivalForest") v.out <- rsf(Survrsf(time, status)~., veteran, ntree = 1000) plot.error(v.out, veteran)