PredictorClient.fpRecommendScore
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The read-only fpRecommendScore property returns the Recommendation Score, which measures the quality of a ranked list of recommendations returned from a prediction model.
Definition
Property fpRecommendScore As Single
Parameters
None.
Error Values
This method sets the Number property of the global Err object to S_OK (&H00000000) to indicate success and to standard COM error values to indicate failure. For more information about standard COM errors, see Standard COM Errors. Additional information may be available using the global Err object. In particular, the Description property may contain a text description of the error.
Remarks
Use the Recommendation Score to test and adjust the input parameters for a prediction model. Known cases, taken from the input cases used to build the model, are tested against the prediction model with one of the transactions randomly removed. A list of recommendations is returned, and the prediction is deemed successful if the removed transaction is on the list. The score is the percentage of cases in which the model was successful.
The Recommendation Score is automatically computed when a model is built, using a fraction of the data as test data. The amount of data to set aside for testing purposes is specified as the Measured Accuracy Sample Fraction. For more information, see Building a New Analysis Model and PredictorModels Table.
Load the prediction model using the LoadModelFromDB or LoadModelFromFile methods prior to accessing this property.
For more information about memory ownership issues related to COM property and method parameters, see Managing COM Parameter Memory.