Decision Tree Properties :: SAS® Visual Analytics 7.4: User's Guide

Name

enables you to specify the name for this model.

Maximum branches

specifies the maximum number of branches allowed when splitting a node.

Maximum levels

specifies the maximum depth of the decision tree.

Leaf size

specifies the minimum number of observations allowed in a leaf node.

Response bins

specifies the number of bins used to categorize a measure response variable.

Predictor bins

specifies the number of bins used to categorize a predictor that is a measure variable.

Pruning

specifies the aggressiveness of the tree pruning algorithm. A more aggressive algorithm creates a smaller decision tree. Larger values are more aggressive.

Rapid growth

enables you to use the information gain ratio and k-means fast search methods for decision tree growth. When disabled, the information gain and greedy search methods are used, which generally produce a larger tree and require more time to create.

Include missing

enables you to include observations with missing values. For category variables, a missing value is assigned to its own level. For measure variables, a missing value is assigned to the smallest available machine value (negative infinity).

Reuse predictors

allows more than one split in the same branch based on a predictor.

Frequency

specifies whether nodes report how many observations they contain or what percentage of the observations they contain.

Assessment

Use default number of bins specifies whether you want to use the default number of bins or to set your own value. By default, measure variables are grouped into 20 bins.
Number specifies the number of bins to use when the Use default number of bins property is not selected. You must specify an integer value between 5 and 100.
Prediction cutoff specifies the value at which a computed probability is considered an event.
Tolerance specifies the tolerance value that is used to determine the convergence of the iterative algorithm that estimates the percentiles. Specify a smaller value to increase the algorithmic precision.

Show diagnostic plots

specifies whether the Leaf Statistics and Assessment windows appear in the model pane.

Show tree overview

displays the tree overview. The tree overview enables quick navigation of large decision trees. When you zoom in to view a specific area of the decision tree, the tree overview shows the entire decision tree and highlights the area that you are viewing. You can click and drag the highlighted area to change the display of the decision tree. Click zoom to fit icon

in the upper left corner of the tree overview to view the entire decision tree. Click minimize tree icon

in the upper left corner of the tree overview to minimize the tree overview.