DMSCHEMA_MINING_SERVICES Rowset

Provides a description of each data mining algorithm that the provider supports.

Rowset Columns

The DMSCHEMA_MINING_SERVICES rowset contains the following columns.

Column name Type indicator Description
SERVICE_NAME DBTYPE_WSTR The name of the algorithm. This column is provider-specific.
SERVICE_TYPE_ID DBTYPE_UI4 This column contains a bitmap that describes the mining service. Microsoft SQL Server Analysis Services populates this column with one of the following values:

DM_SERVICETYPE_CLASSIFICATION (1)

DM_SERVICETYPE_CLUSTERING (2)
SERVICE_DISPLAY_NAME DBTYPE_WSTR A localizable display name for the algorithm.
SERVICE_GUID DBTYPE_GUID The GUID for the algorithm.
DESCRIPTION DBTYPE_WSTR A user-friendly description of the algorithm.
PREDICTION_LIMIT DBTYPE_UI4 The maximum number of predictions the model and algorithm can provide.
SUPPORTED_DISTRIBUTION_FLAGS DBTYPE_WSTR A comma-delimited list of flags that describe the statistical distributions supported by the algorithm. This column contains one or more of the following values:

"NORMAL"

"LOG NORMAL"

"UNIFORM"
SUPPORTED_INPUT_CONTENT_TYPES DBTYPE_WSTR A comma-delimited list of flags that describe the input content types that are supported by the algorithm. This column contains one or more of the following values:

"KEY"

"DISCRETE"

"CONTINUOUS"

"DISCRETIZED"

"ORDERED"

"KEY SEQUENCE"

"CYCLICAL"

"PROBABILITY"

"VARIANCE"

"STDEV"

"SUPPORT"

"PROBABILITY VARIANCE"

"PROBABILITY STDEV"

"KEY TIME"
SUPPORTED_PREDICTION_CONTENT_TYPES DBTYPE_WSTR A comma-delimited list of flags that describe the prediction content types that are supported by the algorithm. This column contains one or more of the following values:

"KEY"

"DISCRETE"

"CONTINUOUS"

"DISCRETIZED"

"ORDERED"

"KEY SEQUENCE "

"CYCLICAL"

"PROBABILITY"

"VARIANCE"

"STDEV"

"SUPPORT"

"PROBABILITY VARIANCE"

"PROBABILITY STDEV"

"KEY TIME"
SUPPORTED_MODELING_FLAGS DBTYPE_WSTR A comma-delimited list of the modeling flags that are supported by the algorithm. This column contains one or more of the following values:

"MODEL_EXISTENCE_ONLY"

"REGRESSOR"



Note that provider-specific flags can also be defined.
SUPPORTED_SOURCE_QUERY DBTYPE_WSTR This column is supported for backward compatibility.
TRAINING_COMPLEXITY DBTYPE_I4 The length of time that training is expected to take:

DM_TRAINING_COMPLEXITY_LOW indicates that the running time is relatively short, and it is proportional to input.

DM_TRAINING_COMPLEXITY_MEDIUM indicates that the running time may be long, but it is generally proportional to input.

DM_TRAINING_COMPLEXITY_HIGH indicates that the running time is long and it may grow exponentially in relationship to the number of training cases.
PREDICTION_COMPLEXITY DBTYPE_I4 The length of time that prediction is expected to take:

DM_PREDICTION_COMPLEXITY_LOW indicates that the running time is relatively short, and it is proportional to input.

DM_PREDICTION_COMPLEXITY_MEDIUM indicates that the running time may be long, but it is generally proportional to input.

DM_PREDICTION_COMPLEXITY_HIGH indicates that the running time is long and it may grow exponentially in relationship to the number of training cases.
EXPECTED_QUALITY DBTYPE_I4 The expected quality of the model produced with this algorithm:

DM_EXPECTED_QUALITY_LOW

DM_EXPECTED_QUALITY_MEDIUM

DM_EXPECTED_QUALITY_HIGH
SCALING DBTYPE_I4 The scalability of the algorithm:

DM_SCALING_LOW

DM_SCALING_MEDIUM

DM_SCALING_HIGH
ALLOW_INCREMENTAL_INSERT DBTYPE_BOOL A Boolean that indicates whether the algorithm supports incremental training, i.e., updating the discovered patterns based on new factual data, rather than fully re-discovering the patterns.
ALLOW_PMML_INITIALIZATION DBTYPE_BOOL A Boolean that indicates whether mining models can be created based on an PMML 2.1 string.

If TRUE, the mining algorithm supports initialization from PMML 2.1 content.
CONTROL DBTYPE_I4 The support given by the service if training is interrupted:

DM_CONTROL_NONE indicates that the algorithm cannot be canceled after it starts to train the model.

DM_CONTROL_CANCEL indicates that the algorithm can be canceled after it starts to train the model, but must be restarted to resume training.

DM_CONTROL_SUSPENDRESUME indicates that the algorithm can be canceled and resumed at any time, but results are not available until training is complete.

DM_CONTROL_SUSPENDWITHRESULT indicates that the algorithm can be canceled and resumed at any time, and any incremental results can be obtained.
ALLOW_DUPLICATE_KEY DBTYPE_BOOL A Boolean that indicates whether cases can contain duplicate keys.

If VARIANT_TRUE, cases are allowed to contain duplicate keys.
VIEWER_TYPE DBTYPE_WSTR The recommended viewer for this model.
HELP_FILE DBTYPE_WSTR (Optional) The name of the file that contains the documentation for this service.
HELP_CONTEXT DBTYPE_I4 (Optional) The Help context ID for this service.
MSOLAP_SUPPORTS_ANALYSIS_SERVICES_DDL DBTYPE_WSTR The version of DDL supported. 0 indicates no DDL support.
MSOLAP_SUPPORTS_OLAP_MINING_MODELS DBTYPE_BOOL A Boolean that indicates whether OLAP mining models can be created.

If TRUE, OLAP mining models can be created. Requires MSOLAP_SUPPORTS_ANALYSIS_SERVICES_DDL to be non-zero.
MSOLAP_SUPPORTS_DATA_MINING_DIMENSIONS DBTYPE_BOOL A Boolean that indicates whether data mining dimensions can be created.

If TRUE, data mining dimensions can be created.
MSOLAP_SUPPORTS_DRILLTHROUGH DBTYPE_BOOL A Boolean that indicates whether the service supports drillthrough capabilities.

If TRUE, the service supports drill-through capabilities.

Restriction Columns

The DMSCHEMA_MINING_SERVICES rowset can be restricted on the columns listed in the following table.

Column name Type indicator Restriction State
SERVICE_NAME DBTYPE_WSTR Optional.
SERVICE_TYPE_ID DBTYPE_UI4 Optional.

See Also

Data Mining Schema Rowsets