Decision tree builds regression or classification models in the form of a tree structure. It breaks down a dataset into smaller and smaller subsets while at the same time an associated decision tree is incrementally developed. The result is a tree with decision nodes and leaf nodes. The topmost decision node in a tree which corresponds to the best predictor is called root node.
Following are the steps to apply Decision Tree node in pipeline:
1. Double-click the Decision Tree node. The properties page is displayed.
- Click Edit Properties to edit the properties and click Save.
3. Click Normalizations. The list of normalizations are displayed.
- Click Add Normalization, enter the required normalization properties.
- Click Save.
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