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DMSCHEMA_MINING_SERVICES Rowset

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

The DMSCHEMA_MINING_SERVICES rowset contains the following columns.

Column name

Type indicator

Length

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"

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.

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.

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