varImpPlot

From randomForest v4.6-14 by Andy Liaw

Variable Importance Plot

Dotchart of variable importance as measured by a Random Forest

Keywords: regression, classif, tree

Usage

varImpPlot(x, sort=TRUE, n.var=min(30, nrow(x$importance)),
           type=NULL, class=NULL, scale=TRUE, 
           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.)
type, class, scale: arguments to be passed on to importance
main: plot title.
...: Other graphical parameters to be passed on to dotchart.

Value

Invisibly, the importance of the variables that were plotted.

Examples

# NOT RUN {
set.seed(4543)
data(mtcars)
mtcars.rf <- randomForest(mpg ~ ., data=mtcars, ntree=1000, keep.forest=FALSE,
                          importance=TRUE)
varImpPlot(mtcars.rf)
# }

Documentation reproduced from package randomForest, version 4.6-14, License: GPL (>= 2)

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