# Documentation

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# cutvar

Class: classregtree

Cut variable names

`classregtree` will be removed in a future release. See `fitctree`, `fitrtree`, `ClassificationTree`, or `RegressionTree` instead.

## Syntax

```v = cutvar(t) v = cutvar(t,nodes) [v,num] = cutvar(...) ```

## Description

`v = cutvar(t)` returns an n-element cell array `v` of the names of the variables used for branching in each node of the tree `t`, where n is the number of nodes. These variables are sometimes known as cut variables. For leaf nodes, `v` contains an empty character vector.

`v = cutvar(t,nodes)` takes a vector `nodes` of node numbers and returns the cut variables for the specified nodes.

`[v,num] = cutvar(...)` also returns a vector `num` containing the number of each variable.

## Examples

Create a classification tree for car data:

```load carsmall t = classregtree([MPG Cylinders],Origin,... 'names',{'MPG' 'Cyl'},'cat',2) t = Decision tree for classification 1 if Cyl=4 then node 2 elseif Cyl in {6 8} then node 3 else USA 2 if MPG<31.5 then node 4 elseif MPG>=31.5 then node 5 else USA 3 if Cyl=6 then node 6 elseif Cyl=8 then node 7 else USA 4 if MPG<21.5 then node 8 elseif MPG>=21.5 then node 9 else USA 5 if MPG<41 then node 10 elseif MPG>=41 then node 11 else Japan 6 if MPG<17 then node 12 elseif MPG>=17 then node 13 else USA 7 class = USA 8 class = France 9 class = USA 10 class = Japan 11 class = Germany 12 class = Germany 13 class = USA view(t)```

```[v,num] = cutvar(t) v = 'Cyl' 'MPG' 'Cyl' 'MPG' 'MPG' 'MPG' '' '' '' '' '' '' '' num = 2 1 2 1 1 1 0 0 0 0 0 0 0```

## References

[1] Breiman, L., J. Friedman, R. Olshen, and C. Stone. Classification and Regression Trees. Boca Raton, FL: CRC Press, 1984.