# tree.control

##### Select Parameters for Tree

A utility function for use with the `control`

argument of `tree`

.

- Keywords
- tree

##### Usage

`tree.control(nobs, mincut = 5, minsize = 10, mindev = 0.01)`

##### Arguments

- nobs
The number of observations in the training set.

- mincut
The minimum number of observations to include in either child node. This is a weighted quantity; the observational weights are used to compute the ‘number’. The default is 5.

- minsize
The smallest allowed node size: a weighted quantity. The default is 10.

- mindev
The within-node deviance must be at least this times that of the root node for the node to be split.

##### Details

This function produces default values of `mincut`

and
`minsize`

, and ensures that `mincut`

is at most half
`minsize`

.

To produce a tree that fits the data perfectly, set `mindev = 0`

and `minsize = 2`

, if the limit on tree depth allows such a tree.

##### Value

A list:

The maximum of the input or default `mincut`

and 1

The maximum of the input or default `minsize`

and 2.

A estimate of the maximum number of nodes that might be grown.

The input `nobs`

.

##### Note

The interpretation of `mindev`

given here is that of Chambers and
Hastie (1992, p. 415), and apparently not what is actually implemented
in S. It seems S uses an absolute bound.

##### References

Chambers, J. M. and Hastie, T. J. (1992)
*Statistical Models in S*. Wadsworth & Brooks/Cole.

##### See Also

*Documentation reproduced from package tree, version 1.0-40, License: GPL-2 | GPL-3*