plot.gg_vimp: Plot a `gg_vimp` object, extracted variable importance of a `rfsrc` object

Description

Plot a gg_vimp object, extracted variable importance of a rfsrc object

Usage

"plot"(x, relative, lbls, ...)

Arguments

gg_vimp object created from a rfsrc object

relative

should we plot vimp or relative vimp. Defaults to vimp.

lbls

A vector of alternative variable labels. Item names should be the same as the variable names.

...

optional arguments passed to gg_vimp if necessary

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.

Examples

Run this code

## Not run: 
# ## ------------------------------------------------------------
# ## classification example
# ## ------------------------------------------------------------
# ## -------- iris data
# # rfsrc_iris <- rfsrc(Species ~ ., data = iris)
# data(rfsrc_iris, package="ggRandomForests")
# gg_dta <- gg_vimp(rfsrc_iris)
# plot(gg_dta)
#  
# ## ------------------------------------------------------------
# ## regression example
# ## ------------------------------------------------------------
# ## -------- air quality data 
# # rfsrc_airq <- rfsrc(Ozone ~ ., airquality)
# data(rfsrc_airq, package="ggRandomForests")
# gg_dta <- gg_vimp(rfsrc_airq)
# plot(gg_dta)
# 
# ## -------- Boston data
# data(rfsrc_Boston, package="ggRandomForests")
# gg_dta <- gg_vimp(rfsrc_Boston)
# plot(gg_dta)
# 
# ## -------- mtcars data
# data(rfsrc_mtcars, package="ggRandomForests")
# gg_dta <- gg_vimp(rfsrc_mtcars)
# plot(gg_dta)
# 
# ## ------------------------------------------------------------
# ## survival example
# ## ------------------------------------------------------------
# ## -------- veteran data
# data(rfsrc_veteran, package="ggRandomForests")
# gg_dta <- gg_vimp(rfsrc_veteran)
# plot(gg_dta)
# 
# ## -------- pbc data
# data(rfsrc_pbc, package="ggRandomForests")
# gg_dta <- gg_vimp(rfsrc_pbc)
# plot(gg_dta)
# 
# ## End(Not run)