ggRandomForests (version 2.0.1)

plot.gg_rfsrc: Predicted response plot from a gg_rfsrc object.

Description

Plot the predicted response from a gg_rfsrc object, the rfsrc prediction, using the OOB prediction from the forest.

Usage

"plot"(x, ...)

Arguments

x

gg_rfsrc object created from a rfsrc object

...

arguments passed to gg_rfsrc.

Value

ggplot object

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_rfsrc rfsrc

Examples

## Not run: 
# ## ------------------------------------------------------------
# ## classification example
# ## ------------------------------------------------------------
# ## -------- iris data
# # rfsrc_iris <- rfsrc(Species ~ ., data = iris)
# data(rfsrc_iris, package="ggRandomForests")
# gg_dta<- gg_rfsrc(rfsrc_iris)
# 
# plot(gg_dta)
# 
# ## ------------------------------------------------------------
# ## Regression example
# ## ------------------------------------------------------------
# ## -------- air quality data
# # rfsrc_airq <- rfsrc(Ozone ~ ., data = airquality, na.action = "na.impute")
# data(rfsrc_airq, package="ggRandomForests")
# gg_dta<- gg_rfsrc(rfsrc_airq)
# 
# plot(gg_dta)
# 
# ## -------- Boston data
# data(rfsrc_Boston, package="ggRandomForests")
# plot(rfsrc_Boston) 
# 
# ## -------- mtcars data
# data(rfsrc_mtcars, package="ggRandomForests")
# gg_dta<- gg_rfsrc(rfsrc_mtcars)
# 
# plot(gg_dta)
# 
# ## ------------------------------------------------------------
# ## Survival example
# ## ------------------------------------------------------------
# ## -------- veteran data
# ## randomized trial of two treatment regimens for lung cancer
# # data(veteran, package = "randomForestSRC")
# # rfsrc_veteran <- rfsrc(Surv(time, status) ~ ., data = veteran, ntree = 100)
# data(rfsrc_veteran, package = "ggRandomForests")
# gg_dta <- gg_rfsrc(rfsrc_veteran)
# plot(gg_dta)
# 
# gg_dta <- gg_rfsrc(rfsrc_veteran, conf.int=.95)
# plot(gg_dta)
# 
# gg_dta <- gg_rfsrc(rfsrc_veteran, by="trt")
# plot(gg_dta)
# 
# ## -------- pbc data
# data(rfsrc_pbc, package = "ggRandomForests")
# gg_dta <- gg_rfsrc(rfsrc_pbc)
# plot(gg_dta)
# 
# gg_dta <- gg_rfsrc(rfsrc_pbc, conf.int=.95)
# plot(gg_dta)
# 
# gg_dta <- gg_rfsrc(rfsrc_pbc, by="treatment")
# plot(gg_dta)
# 
# 
# ## End(Not run)