prune

Produce sequence of classification subtrees by pruning

Syntax

tree1 = prune(tree) tree1 = prune(tree,Name,Value)

Description

tree1 = prune(tree) creates a copy of the classification tree tree with its optimal pruning sequence filled in.

tree1 = prune(tree,Name,Value) creates a pruned tree with additional options specified by one Name,Value pair argument. You can specify several name-value pair arguments in any order as Name1,Value1,…,NameN,ValueN.

Input Arguments

tree

A classification tree created with fitctree.

Name-Value Pair Arguments

Specify optional comma-separated pairs of Name,Value arguments. Name is the argument name and Value is the corresponding value. Name must appear inside quotes. You can specify several name and value pair arguments in any order as Name1,Value1,...,NameN,ValueN.

`'Alpha'`	A numeric scalar. `prune` prunes `tree` to the specified value of the pruning cost.
`'Level'`	A numeric scalar from `0` (no pruning) to the largest pruning level of this tree `max(tree.PruneList)`. `prune` returns the tree pruned to this level.
`'Nodes'`	A numeric vector with elements from `1` to `tree.NumNodes`. Any `tree` branch nodes listed in `nodes` become leaf nodes in `tree1`, unless their parent nodes are also pruned.

Output Arguments

tree1

A classification tree.

Examples

expand all

Prune and Display a Classification Tree

Open Live Script

Construct and display a full classification tree for Fisher's iris data.

load fisheriris;
varnames = {'SL','SW','PL','PW'};
t1 = fitctree(meas,species,'MinParentSize',5,'PredictorNames',varnames);
view(t1,'Mode','graph');

Construct and display the next largest tree from the optimal pruning sequence.

t2 = prune(t1,'Level',1);
view(t2,'Mode','graph');

Tips

tree1 = prune(tree) returns the decision tree tree1 that is the full, unpruned tree, but with optimal pruning information added. This is useful only if you created tree by pruning another tree, or by using the fitctree function with pruning set 'off'. If you plan to prune a tree multiple times along the optimal pruning sequence, it is more efficient to create the optimal pruning sequence first.

Documentation