5.4.5 - Tree Pruning - Teradata Warehouse Miner

Teradata Warehouse Miner User Guide - Volume 3Analytic Functions

Product
Teradata Warehouse Miner
Release Number
5.4.5
Published
February 2018
Language
English (United States)
Last Update
2018-05-04
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On both the Tree Browser and Text Tree, passing the mouse over a node or rule results in a hyperlink indication. When Tree Pruning is enabled, the following menu appears.

Tree Pruning menu

Clicking on a node or rule highlights the node and all subnodes, indicating which portion of the tree will be pruned. Additionally, the Prune Selected Branch option becomes enabled as follows.
Tree Pruning Menu > Prune Selected Branch

Clicking on Prune Selected Branch converts the highlighted node to a leaf node, and all subnodes disappear. When this is done, the other two Tree Pruning options become enabled.
Tree Pruning menu (All Options Enabled)

Click on Undo Last Prune to revert back to the original tree, or the previously pruned tree if Prune Selected Branch was done multiple times. Click on Save Pruned Tree to save the tree to XML. This will be saved in metadata and can be rescored in a future release.

After a tree is manually pruned and saved to metadata using the Save Pruned Tree option, it can be reopened and viewed in the Tree Browser and, if desired, pruned further. (All additional prunes must be re-saved to metadata). A previously pruned tree will be labeled to distinguish it from a tree that has not been manually pruned.
Decision Tree Graph: Previously Pruned Tree

“More >>”

On both the Tree Browser and Text Tree, if Gini Index has been selected for Tree Splitting, large surrogate splits may occur. If a surrogate split is proceeded by “more >>”, the entire surrogate split can be displayed in a separate pop-up screen by clicking on the node and/or rule as follows.

Decision Tree Graph: Predicate

Lift Chart

This graph displays the statistic in the Cumulative Lift Table, with the following options:
  • Non-Cumulative
    • % Response — This column contains the percentage of observations in the decile where the actual value of the dependent variable is 1.
    • % Captured Response — This column contains the percentage of responses in the decile over all the responses in any decile.
    • Lift — The lift value is the percentage response in the decile (Pct Response) divided by the expected response, where the expected response is the percentage of response or dependent 1-values over all observations. For example, if 10% of the observations overall have a dependent variable with value 1, and 20% of the observations in decile 1 have a dependent variable with value 1, then the lift value within decile 1 is 2.0, meaning that the model gives a “lift” that is better than chance alone by a factor of two in predicting response values of 1 within this decile.
  • Cumulative
    • % Response — This is a cumulative measure of the percentage of observations in the decile where the actual value of the dependent variable is 1, from decile 1 to this decile.
    • % Captured Response — This is a cumulative measure of the percentage of responses in the decile over all the responses in any decile, from decile 1 to this decile.
    • Cumulative Lift — This is a cumulative measure of the percentage response in the decile (Pct Response) divided by the expected response, where the expected response is the percentage of response or dependent 1-values over all observations, from decile 1 to this decile.

Any combination of options can be displayed as follows.

Decision Tree Graph: Lift