getTree {randomForest}R Documentation

Extract a single tree from a forest.

Description

This function extract the structure of a tree from a randomForest object.

Usage

getTree(rfobj, k=1)

Arguments

rfobj a randomForest object.
k which tree to extract?

Details

For categorical predictors, the splitting point is represented by an integer, whose binary expansion gives the identities of the categories that goes to left or right. For example, if a predictor has three categories, and the split point is 5. The binary expansion of 5 is (1, 0, 1) (because 5 = 1*2^0 + 0*2^1 + 1*2^2), so cases with categories 1 or 3 in this predictor get sent to the left, and the rest to the right.

Value

A matrix with six columns and number of rows equal to total number of nodes in the tree. The six columns are:

left daughter the row where the left daughter node is; 0 if the node is terminal
right daughter the row where the right daughter node is; 0 if the node is terminal
split var which variable was used to split the node; 0 if the node is terminal
split point where the best split is; see Details for categorical predictor
status is the node terminal (-1) or not (1)
prediction the prediction for the node; 0 if the node is not terminal

Author(s)

Andy Liaw andy_liaw@merck.com

See Also

randomForest

Examples

data(iris)
## Look at the third trees in the forest.
getTree(randomForest(iris[,-5], iris[,5], ntree=10), 3)

[Package randomForest version 4.5-1 Index]