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

### 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]