Jump to the list of stored procedures for each mining model type What are the data mining stored procedures?
The system stored procedures for data mining that are provided in Analysis Services were created for internal use, in order to efficiently work with mining model content and mining model attributes within the data mining model viewers. However, these stored procedures are useful when you want to experiment with results or to explore the model. You might use these stored procedures to simplify queries against a data mining model, or to create custom visualizations.
How do I use them?
These system stored procedures can be called from code or from a DMX query (using the CALL syntax). In addition to the system stored procedures that are provided in Analysis Services, you can download additional custom stored procedures that have been provided as samples by the data mining development team, or download stored procedures that have been provided by the community. To use new stored procedures within an instance of SQL Server, you must have permissions to create managed .NET assemblies on the instance. For more information about how to create and register new assemblies, see Creating Stored Procedures (Analysis Services) in the MSDN Library.
The syntax in the following examples always shows the shortest name that you can used to reference the stored procedure. These examples have all been tested using the Adventure Works sample mining models and calling the procedure from a DMX query window.
The fully qualified name is the name that you would use to reference the stored procedure from custom code, but these references have not been tested.
Sample models
If you don’t have models to experiment with, you can build models by using the SQL Server samples:
NOTE: Microsoft reserves the right to change internal stored procedures at any time. Although the stored procedures for data mining are described here for your convenience, Microsoft does not support their use in a production environment. To ensure stability and compatibility in a production environment, you should always write your own queries by using DMX.
General Procedures for All Model Types
GetAttributeValues GetModelAttributes
GetAttributeValues
GetModelAttributes
Clustering Models
GetClusterCharacteristics GetClusterDiscrimination GetClusterProfiles GetClusters
GetClusterCharacteristics
GetClusterDiscrimination
GetClusterProfiles
GetClusters
Sequence Clustering Models
GetClusters GetClusterProfiles GetClusterCharacteristics GetClusterDiscrimination
Association Models
ARGetNodes GetItemsets GetRules GetStatistics
ARGetNodes
GetItemsets
GetRules
GetStatistics
Decision Tree and Linear Regression Models
CalculateTreeDepth DTAddNodes DTGetNodeGraph DTGetNodes GetTreeScores
CalculateTreeDepth
DTAddNodes
DTGetNodeGraph
DTGetNodes
GetTreeScores
Naïve Bayes Models
GetAttributeCharacteristics GetAttributeDiscrimination GetAttributeHistogram GetPredictableAttributes
GetAttributeCharacteristics
GetAttributeDiscrimination
GetAttributeHistogram
GetPredictableAttributes
Neural Networks and Logistic Regression Models
GetAttributeScores GetAttributeValues
GetAttributeScores
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