rxDForestUtils: Utility Functions for rxDForest
Description
Utility Functions for rxDForest.
Usage
rxVarImpPlot(x, sort = TRUE, n.var = 30, main = deparse(substitute(x)), ... )
rxLeafSize(x, use.weight = TRUE)
rxTreeDepth(x)
rxTreeSize(x, terminal = TRUE)
rxVarUsed(x, by.tree = FALSE, count = TRUE)
rxGetTree(x, k = 1)
Arguments
x
an object of class rxDForest or rxDTree.
sort
logical value. If TRUE, the variables will be sorted in decreasing importance.
n.var
an integer specifying the number of variables to show when sort=FALSE.
main
a character string specifying the main title for the plot.
...
other arguments to be passed on to dotchart.
use.weight
logical value. If TRUE, the leaf size is measured by the total weight of its observations instead of the total number of its observations.
terminal
logical value. If TRUE, only the terminal nodes will be counted.
by.tree
logical value. If TRUE, the list of variables used will be broken down by trees.
count
logical value. If TRUE, the frequencies that variables appear in trees will be returned.
k
an integer specifying the index of the tree to be extracted.
Value
rxVarImpPlot- plots a dotchart of the variable importance as measured by the decision forest.rxLeafSize- returns the size of the terminal nodes in the decision forest.rxTreeDepth- returns the depth of trees in the decision forest.rxTreeSize- returns the size of trees in terms of the number of nodes in the decision forest.rxVarUsed- finds out the variables actually used in the decision forest.rxGetTree- extracts a single tree from the decision forest.
Author(s)
Microsoft Corporation Microsoft Technical Support
References
See Also
Examples
set.seed(1234)
# classification
iris.sub <- c(sample(1:50, 25), sample(51:100, 25), sample(101:150, 25))
iris.dforest <- rxDForest(Species ~ Sepal.Length + Sepal.Width + Petal.Length + Petal.Width,
data = iris[iris.sub, ], importance = TRUE)
rxVarImpPlot(iris.dforest)
rxTreeSize(iris.dforest)
rxVarUsed(iris.dforest)
rxGetTree(iris.dforest)