Property Name
|
Description
|
---|---|
Model function
|
Specifies the type of output that your predictive model project generates. The Model
function property that you specify affects the model templates that are provided when you are ready to import models into a project. After it has
been declared, the Model function property for a project cannot be changed. Ensure that the types of models that you
are going to use in the project fit within the selected model function type. For
more information about the types of model functions, see Types of Model Functions.
|
Operation
status
|
Specifies the current
state of the project:
Under Development
indicates that the project has started but a champion model is not yet in production.
Active
indicates that a champion model for this project is in production.
Inactive
indicates that the champion model is temporarily suspended from production.
Retired
indicates that the champion model for this project is no longer in production.
To set the status, select
an option from the Operation status drop-down list.
|
Lock project
variables
|
Specifies that the project metadata is locked and the project definition cannot be
modified. For more information, see
Lock or Unlock Project Variables.
|
Model Function
|
Description
|
Example
|
---|---|---|
Analytical
|
Function for any model
that is not Prediction, Classification, or Segmentation.
|
None
|
Classification
|
DEFAULT_RISK =
{Low, Med, High}
|
|
Prediction
|
Function for models that have interval targets with continuous values.
|
The score output of a prediction model could estimate the weight of a person. The output of a model would be P_Weight.
|
Segmentation
|
Function for segmentation or clustering models.
|
Clustering models
|
Property Name
|
Description
|
---|---|
Default
test table
|
Specifies a default SAS data set that can be used to create the New Dynamic Lift and Interval Target Variable reports.
|
Default
scoring input table
|
Specifies a default SAS data set that is used as the input data table for all scoring
tests within the project. If
you specify a value for the Default
scoring input table property, the value is used as the default input table in the Add a New Scoring Test window.
|
Default
scoring output table
|
Specifies a default SAS data set that defines the variables to keep in the scoring results table and the scoring test output table. If you specify a value of the Default scoring output table property,
the value is used as the default output table in the Add
a New Scoring Test window.
|
Default
performance table
|
Specifies the default performance table for all model performance monitoring tests within a project.
|
Default
train table
|
Specifies the default
train table that is used for retraining models and for the Training
Summary Data Set report. The Default train table is also used to validate scoring functions or scoring model files when a user publishes the associated project champion model or challenger models to a database. This property is optional.
|
Champion
version
|
Specifies the version that contains the champion model in a production environment.
|
Model function
|
Specifies the type of output that your predictive model project generates. The Model
function property that you specify affects the model templates that are provided when you
are ready to import models into a project. After it has
been declared, the Model function property for a project cannot be changed. Ensure that the types of models that you
use in the project fit within the selected model function type.
|
Training
target variable
|
Specifies the name of the target variable that was used to train the model.
|
Target event
value
|
Specifies the target variable value that defines the desired target variable event.
|
Class target
values
|
For class, nominal, ordinal, or interval targets, the set of possible outcome classes, separated by
commas. For example, binary class target values might be
1, 0 or Yes , No . Nominal class target values might be Low, Medium,
High . These values are for information only.
|
Class target
level
|
Specifies the class target level of binary, nominal, ordinal, or interval.
|
Output event
probability variable
|
The output event probability
variable name, when the Model function property
is set to Classification or Analytical.
|
Output prediction
variable
|
The output prediction variable name, when the Model function property
is set to Prediction or Analytical.
|
Output segmentation
variable
|
The output segmentation
variable name, when the Model function property
is set to Segmentation or Analytical.
|