Now that
you have verified the input data, it is time to build predictive models.
You will now perform the following tasks to model the input data using
nonparametric decision trees:
-
You will enable SAS Enterprise Miner to automatically
train a full decision tree and to automatically prune the tree to
an optimal size. When training the tree, split rules at each step
are selected to maximize the split decision logworth. Split decision
logworth is a statistic that measures the effectiveness of a particular
split decision at differentiating values of the target variable. For
more information about logworth, see the SAS Enterprise Miner Help.
-
You will interactively train a decision tree. At each
step, you will select from a list of candidate rules to define the
split rule that you deem to be the best.