Main Content

prune

Produce sequence of regression subtrees by pruning

collapse all in page

Syntax

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

Description

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

example

tree1 = prune(tree,Name=Value) creates a pruned tree with additional options specified by a single name-value argument.

Examples

collapse all

Open Live Script

Load the carsmall data set. Consider Horsepower and Weight as predictor variables.

load carsmall;
X = [Weight Horsepower];
varNames = ["Weight" "Horsepower"];

Grow a regression tree using the entire data set. View the tree.

Mdl = fitrtree(X,MPG,PredictorNames=varNames)
Mdl = 
  RegressionTree
           PredictorNames: {'Weight'  'Horsepower'}
             ResponseName: 'Y'
    CategoricalPredictors: []
        ResponseTransform: 'none'
          NumObservations: 94



view(Mdl,Mode="graph");

Figure Regression tree viewer contains an axes object and other objects of type uimenu, uicontrol. The axes object contains 60 objects of type line, text. One or more of the lines displays its values using only markers

The regression tree has 16 pruning levels.

Prune the regression tree to pruning-level 10. View the pruned tree.

MdlPruned = prune(Mdl,Level=10);
view(MdlPruned,Mode="graph");

Figure Regression tree viewer contains an axes object and other objects of type uimenu, uicontrol. The axes object contains 24 objects of type line, text. One or more of the lines displays its values using only markers

The pruned tree has six pruning levels.

Input Arguments

collapse all

Regression tree, specified as a RegressionTree object created using the fitrtree function.

Name-Value Arguments

Specify optional pairs of arguments as Name1=Value1,...,NameN=ValueN, where Name is the argument name and Value is the corresponding value. Name-value arguments must appear after other arguments, but the order of the pairs does not matter.

Example: tree1 = prune(tree,Level=10) prunes the tree to level ten.

Before R2021a, use commas to separate each name and value, and enclose Name in quotes.

Example: tree1 = prune(tree,"Level",10) prunes the tree to level ten.

Pruning cost, specified as a numeric scalar from 0 (no pruning) to 1 (prune to one node). The prune function prunes the tree to minimize the sum of (Alpha times the number of leaf nodes) and a cost (mean squared error).

Use only one of these three name-value arguments at a time: Alpha, Level, or Nodes.

Pruning level, specified as a numeric scalar from 0 (no pruning) to the largest pruning level of this tree max(tree.PruneList). The prune function returns the tree pruned to this level.

Use only one of these three name-value arguments at a time: Alpha, Level, or Nodes.

Branch nodes to turn into leaf nodes, specified as 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.

Use only one of these three name-value arguments at a time: Alpha, Level, or Nodes.

Output Arguments

collapse all

Pruned regression tree, returned as a RegressionTree object.

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 fitrtree 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.

Extended Capabilities

Version History

Introduced in R2011a

See Also