ggRandomForests (version 2.0.1)

plot.gg_error: Plot a gg_error object

Description

A plot of the cumulative OOB error rates of the random forest as a function of number of trees.

Usage

"plot"(x, ...)

Arguments

x

gg_error object created from a rfsrc object

...

extra arguments passed to ggplot functions

Value

ggplot object

Details

The gg_error plot is used to track the convergence of the randomForest. This figure is a reproduction of the error plot from the plot.rfsrc function.

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_error rfsrc plot.rfsrc

Examples

## Not run: 
# ## Examples from RFSRC package... 
# ## ------------------------------------------------------------
# ## classification example
# ## ------------------------------------------------------------
# ## ------------- iris data
# ## You can build a randomForest
# # rfsrc_iris <- rfsrc(Species ~ ., data = iris)
# # ... or load a cached randomForestSRC object
# data(rfsrc_iris, package="ggRandomForests")
# 
# # Get a data.frame containing error rates
# gg_dta<- gg_error(rfsrc_iris)
# 
# # Plot the gg_error object
# plot(gg_dta)
# 
# ## ------------------------------------------------------------
# ## Regression example
# ## ------------------------------------------------------------
# ## ------------- airq data
# # rfsrc_airq <- rfsrc(Ozone ~ ., data = airquality, na.action = "na.impute")
# # ... or load a cached randomForestSRC object
# data(rfsrc_airq, package="ggRandomForests")
# 
# # Get a data.frame containing error rates
# gg_dta<- gg_error(rfsrc_airq)
# 
# # Plot the gg_error object
# plot(gg_dta)
# 
# ## ------------- Boston data
# data(rfsrc_Boston, package="ggRandomForests")
# 
# # Get a data.frame containing error rates
# gg_dta<- gg_error(rfsrc_Boston)
# 
# # Plot the gg_error object
# plot(gg_dta)
# 
# ## ------------- mtcars data
# data(rfsrc_mtcars, package="ggRandomForests")
# 
# # Get a data.frame containing error rates
# gg_dta<- gg_error(rfsrc_mtcars)
# 
# # Plot the gg_error object
# 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)
# 
# # Load a cached randomForestSRC object
# data(rfsrc_veteran, package="ggRandomForests")
# 
# gg_dta <- gg_error(rfsrc_veteran)
# plot(gg_dta)
# 
# ## ------------- pbc data
# # Load a cached randomForestSRC object
# data(rfsrc_pbc, package="ggRandomForests")
# 
# gg_dta <- gg_error(rfsrc_pbc)
# plot(gg_dta)
# ## End(Not run)