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Default
Scoring Task Input Table
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Specifies a default
SAS data set that is used as the input data table for all of scoring
tasks within the SAS Model Manager project. The model's Default
Scoring Task Input Table property inherits the property
value from the associated version or project, if one is specified.
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Default
Scoring Task Output Table
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Specifies a default
SAS data set that defines the variables to keep in the scoring results
table and the scoring task output table. The model's Default
Scoring Task Output Table property inherits the property
value from the associated version or project, if one is specified.
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Default
Performance Table
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Specifies the default
performance table for all model performance monitoring tasks within
a SAS Model Manager project.
A model's Default
Performance Table property inherits the property value
from the associated version or project, if one is specified. If you
do not specify a performance table, some of the SAS Model Manager
Model Monitoring reports might not be enabled.
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The train table is optional
and is used only as information. However, when a value is specified
for a model's Default Train Table property,
SAS Model Manager does the following:
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uses default train table to validate
scoring functions or scoring model files when a user publishes the
associated project champion model or challenger models to a database.
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checks the Validate
scoring results box in the Publish Scoring
Function window.
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Specifies a date property
by which the selected model is obsolete or needs to be updated or
replaced. This property is for informational purposes and is not associated
with any computational action by SAS Model Manager. This property
is optional.
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Specifies a text string
that is used as a label for the selected model in the model assessment
charts that SAS Model Manager creates. If no value is provided for
the Model Label property, SAS Model Manager
uses the text string that is specified for the Model Name property.
The Model Label property can be useful if
the Model Name property that is specified is too long for use in plots.
This property is optional.
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Specifies a text string
that is used to provide an additional description for a model, such
as a promotional or campaign code. This property is for informational
purposes and is not associated with any computational action by SAS
Model Manager. This property is optional.
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Specifies the computational
algorithm that is used for the selected model. This property cannot
be modified.
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Specifies the SAS Model
Manager function class that was chosen when the SAS Model Manager
associated project was created. The Function property
specifies the type of output that models in the predictive model project
generate. For more information,
see Overview of Importing Models.
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Specifies the Modeler
ID or, when Modeler ID is missing, specifies the user ID of the individual
who created the model that is stored in the SPK file for SAS Enterprise
Miner models. Otherwise, the modeler can be specified during model
import for local files into SAS Model Manager.
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Specifies whether the
imported model came from SAS Enterprise Miner or from other modeling
tools.
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Specifies the version
number of the tool that is specified in the Tool property.
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Specifies whether the
imported model score code is a DATA step fragment, ready-to-run SAS
code, or a PMML file. Valid values are DATAStep, SAS
Program, and PMML.
Note: If the model is created using
PMML 4.0, the Score Code Type is DATA
step and not PMML.
Note: SAS Model Manager cannot
export or publish models whose Score Code Type model
property is set to SAS Program.
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Specifies the SAS Model
Manager model template that was used to import the model and to create
pointers to its component files and metadata.
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Specifies where the
original model is if this model is copied from another model in the
SAS Model Manager repository.
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Specifies the name
of the target variable for a classification or prediction model. This
property can be ignored for segmentation, cluster, and other models
that do not use target variables. For example, if a model predicts
when GENDER=M, then the target variable value is GENDER.
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Specifies a value for
the target event that the model attempts to predict. This property
is used only when a value is specified for the Target
Variable property. For example, if a model predicts when
GENDER=M, then the target event value is M.
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