plot.gg_roc {ggRandomForests} | R Documentation |
ROC plot generic function for a gg_roc
object.
Description
ROC plot generic function for a gg_roc
object.
Usage
## S3 method for class 'gg_roc'
plot(x, which_outcome = NULL, ...)
Arguments
x |
|
which_outcome |
for multiclass problems, choose the class for plotting |
... |
arguments passed to the |
Value
ggplot
object of the ROC curve
References
Breiman L. (2001). Random forests, Machine Learning, 45:5-32.
Ishwaran H. and Kogalur U.B. (2007). Random survival forests for R, Rnews, 7(2):25-31.
Ishwaran H. and Kogalur U.B. (2013). Random Forests for Survival, Regression and Classification (RF-SRC), R package version 1.4.
See Also
gg_roc
rfsrc
Examples
## Not run:
## ------------------------------------------------------------
## classification example
## ------------------------------------------------------------
## -------- iris data
#rfsrc_iris <- rfsrc(Species ~ ., data = iris)
data(rfsrc_iris, package="ggRandomForests")
# ROC for setosa
gg_dta <- gg_roc(rfsrc_iris, which_outcome=1)
plot.gg_roc(gg_dta)
# ROC for versicolor
gg_dta <- gg_roc(rfsrc_iris, which_outcome=2)
plot.gg_roc(gg_dta)
# ROC for virginica
gg_dta <- gg_roc(rfsrc_iris, which_outcome=3)
plot.gg_roc(gg_dta)
# Alternatively, you can plot all three outcomes in one go
# by calling the plot function on the forest object.
plot.gg_roc(rfsrc_iris)
## End(Not run)
[Package ggRandomForests version 2.2.1 Index]