Tip
To navigate the decision tree,
you can use the mouse and keyboard. Hold down the
Shift key
and click anywhere in the
Tree window to
move the decision tree within the window. Use your mouse’s
scroll wheel to zoom in and out of the decision tree. Scroll up to
zoom in, and scroll down to zoom out. The zoom is centered on the
position of your cursor.
The color of the
node in the icicle plot indicates the predicted level for that node. When you select a
node in either the
decision tree or the icicle
plot, the corresponding node is selected in the other location. When you select a
leaf node, that node is selected in the
Leaf Statistics window. A legend is available at the bottom
of the model pane.
Right-click inside a node to open a different pop-up menu. The available menu options
depend on whether you clicked a leaf node.
For leaf nodes, you can select from the following menu options:
Split
opens the
Split Decision Tree window. Use this window to select the variable that is used to split the node. Click
OK to
split the node based on the selected variable. Click
Cancel to not split the node. Variables are sorted in
descending order by their
log worth.
Some variables are not available for a split if the value of the split is too small
or the split would
violate the
Leaf size property.
Train
opens the
Train Decision Tree window. Use this window to train more than one level beyond the leaf node. First,
select every variable that you want to be available for training. Only those
variables selected in the
Train Decision Tree window are available
for training. Specify the maximum depth of training in the
Maximum depth of subtree property. Click
OK to train the decision tree.
For other nodes, select
Prune to remove all nodes that follow the selected node. This turns the selected node into
a leaf node. After
pruning a node, you can select
Restore to
undo the
prune.