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The Predict function returns a predicted value, or set of values, for a specified column.

Predict(<scalar column reference>, [option1], [option2],    , [INCLUDE_NODE_ID], n)
Predict(<table column reference>, [option1], [option2],    , [INCLUDE_NODE_ID], n)

Either a scalar column reference or a table column reference.

<scalar column reference>


<table column reference>

The return type depends on the type of column to which this function is applied.


INCLUSIVE, EXCLUSIVE, INPUT_ONLY, and INCLUDE_STATISTICS apply only for a table column reference, and EXCLUDE_NULL and INCLUDE_NULL apply only for a scalar column reference.

The INCLUDE_NODE_ID parameter returns the $NODEID column in the result. NODE_ID is the content node on which the prediction is executed for a particular case. This parameter is optional for the predict on table column.

The n parameter applies to table columns. It sets the number of rows that are returned based on the type of prediction. If the underlying column is sequence, it calls the PredictSequence function. If the underlying column is time series, it calls the PredictTimeSeries function. For associative types of prediction, it calls the PredictAssociation function.

The Predict function supports polymorphism.

The following alternative abbreviated forms are frequently used:

  • [Gender] is an alternative for Predict([Gender], EXCLUDE_NULL).
  • [Products Purchases] is an alternative for Predict([Products Purchases], EXCLUDE_NULL, EXCLUSIVE).
The return type of this function is itself regarded as a column reference. This means that the Predict function can be used as an argument in other functions that take a column reference as an argument (except for the Predict function itself).

Passing INCLUDE_STATISTICS to a prediction on a table-valued column adds the meta columns $Probability and $Support to the resulting table. These columns describe the probability of existence for the associated nested table record.

The following example uses the Predict function to return the four products in the Adventure Works database that are most likely to be sold together. Because the function is predicting against an association rules mining model, it automatically uses the PredictAssociation function as described earlier.

  Predict([Association].[v Assoc Seq Line Items],INCLUDE_STATISTICS,4)