ggRandomForests (version 1.2.1)

gg_vimp.rfsrc: Variable Importance (VIMP) data object

Description

gg_vimp Extracts the variable importance (VIMP) information from a a rfsrc object.

Usage

gg_vimp.rfsrc(object, n_var, ...)

Arguments

object

A rfsrc object or output from vimp

n_var

select a number pf the highest VIMP variables to plot

...

arguments passed to the vimp.rfsrc function if the rfsrc object does not contain importance information.

Value

• gg_vimp object. A data.frame of VIMP measures, in rank order.

References

Ishwaran H. (2007). Variable importance in binary regression trees and forests, Electronic J. Statist., 1:519-537.

See Also

plot.gg_vimp rfsrc vimp

Examples

## ------------------------------------------------------------
## 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)

# Restrict to only the top 10.
gg_dta <- gg_vimp(rfsrc_pbc, n_var=10)
plot(gg_dta)