compact
Compact tree
Syntax
Description
Examples
Create a Compact Classification Tree
Compare the size of the classification tree for Fisher's iris data to the compact version of the tree.
load fisheriris fulltree = fitctree(meas,species); ctree = compact(fulltree); b = whos('fulltree'); % b.bytes = size of fulltree c = whos('ctree'); % c.bytes = size of ctree [b.bytes c.bytes] % shows ctree uses half the memory
ans = 1×2
11931 5266
Input Arguments
tree
— Classification tree
ClassificationTree
object
Classification tree, specified as a ClassificationTree
object.
Use the fitctree
function to create a classification
tree object.
Output Arguments
ctree
— Compact decision tree
CompactClassificationTree
object
Compact decision tree, returned as a CompactClassificationTree
object.
You can predict classifications using ctree
exactly as you can
using tree
. However, since ctree
does not contain
training data, you cannot perform some actions, such as cross validation.
Extended Capabilities
GPU Arrays
Accelerate code by running on a graphics processing unit (GPU) using Parallel Computing Toolbox™.
This function fully supports GPU arrays. For more information, see Run MATLAB Functions on a GPU (Parallel Computing Toolbox).
Version History
Introduced in R2011a
See Also
CompactClassificationTree
| ClassificationTree
| fitctree
| predict
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