Decision Tree Predict VAL

The Predict function predicts the values of the dependent variable in test data. There is an additional required input table that specifies the model used by the VALIB DecisionTree function.

Options

Accumulate
Specifies one or more columns from the 'data' DataFrame that can be passed to the result output DataFrame.
Include Confidence
Specifies whether the output DataFrame contain a column indicating how likely it is, for a particular leaf node on the tree, that the prediction is correct.
Index Columns
Specifies one or more different columns for the primary index of the result output DataFrame.
Response Column
Specifies the name of the predicted value column. If this argument is not specified, the name of the dependent column in 'data' DataFrame is used.
Targeted Value
Specifies whether the result output DataFrame contain a column indicating how likely it is, for a particular leaf node and targeted value of a predicted result with only two values, that the prediction is correct.
Output Schema
Output Schema, if Volatile is true then use user login as the schema.
Output Table
Output Table
VAL Location
VAL Location

Input Ports

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Connection to a Teradata Database Instance
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Decision Tree Predict VAL input
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Decision Tree Predict VAL input

Output Ports

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Decision Tree Predict VAL output

Nodes

Extensions

Links