ggRandomForests (version 2.0.1)

plot.gg_roc: ROC plot generic function for a gg_roc object.

Description

ROC plot generic function for a gg_roc object.

Usage

"plot"(x, which.outcome = NULL, ...)

Arguments

x

gg_roc object created from a classification forest

which.outcome

for multiclass problems, choose the class for plotting

...

arguments passed to the gg_roc function

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)