varImpPlot {randomForest}R Documentation

Variable Importance Plot

Description

Dotchart of variable importance as measured by a Random Forest

Usage

varImpPlot(x, sort=TRUE, n.var=min(30, if(is.null(dim(x$importance)))
           length(x$importance) else nrow(x$importance)),
           class = NULL, scale=TRUE, xlab="Importance", ylab="",
           main=deparse(substitute(x)), ...) 

Arguments

x An object of class randomForest.
sort Should the variables be sorted in decreasing order of importance?
n.var How many variables to show? (Ignored if sort=FALSE.)
class For classification data, an integer or string indicating the class for which variable importance is seeked.
scale For permutation-based measures, should the measures be divided by their ``standard errors''?
xlab label for the x-axis.
ylab label for the y-axis.
main plot title.
... Other graphical parameters.

Value

Invisibly, the importance of the variables.

Author(s)

Andy Liaw andy_liaw@merck.com

See Also

randomForest

Examples

set.seed(4543)
data(mtcars)
mtcars.rf <- randomForest(mpg ~ ., data=mtcars, ntree=1000, keep=FALSE,
                          importance=TRUE)
varImpPlot(mtcars.rf)

[Package randomForest version 4.5-1 Index]