variableImpPlot: Variable importance plot from a random forest

In abcrf: Approximate Bayesian Computation via Random Forests

Variable importance plot from a random forest

Description

variableImpPlot provides a dotchart of variable importance as measured by ranger with the argument importance='impurity'.

Usage

variableImpPlot(object, 
n.var=min(30, length(object$model.rf$variable.importance)),
xlim=NULL, main=NULL)

Arguments

object	an abcrf or regAbcrf object.
n.var	number of variables in the variable importance representation.
xlim	range of the abscissa.
main	an overall title for the variable importance plot.

Value

Invisibly, the importance of the variables that were plotted.

See Also

abcrf, plot.abcrf, plot.regAbcrf

Examples

data(snp)
modindex <- snp$modindex[1:500]
sumsta <- snp$sumsta[1:500,]
data1 <- data.frame(modindex, sumsta)
model.rf <- abcrf(modindex~., data1, ntree=100)
variableImpPlot(model.rf)

abcrf documentation built on Aug. 9, 2022, 5:07 p.m.