Specific Properties for a Project

Specifies a default SAS data set that can be used to create model assessment reports such as dynamic lift charts.

Specifies a default SAS data set that is used as the input data table for all scoring tasks within the SAS Model Manager project. If you specify a value for the Default Scoring Task Input Table property, the value is used as the default input table in the New Scoring Task window.

Specifies a default SAS data set that defines the variables to keep in the scoring results table and the scoring task output table. If you specify a value of the Default Scoring Task Output Table property, the value is used as the default output table in the New Scoring Task window.

Specifies the default performance table for all model performance monitoring tasks within a SAS Model Manager project.

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, it is used to validate scoring functions when a user publishes the associated project champion model to a database.

Specifies the current state of the project:

Specifies the channel that is used, by default, to publish a project. The default channel appears in the Channel box of the Channel Usage window.

Specifies the version that contains the champion model in a production environment.

Specifies the type of output that your predictive model project generates. The Model Function property that you specify affects the model templates that SAS Model Manager provides when you are ready to import models into one of your project's version folders. Once 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.

Specifies any person or group that has an interest in the project. For example, an interested party would be the business department or the business analyst whose request led to the creation of a SAS Model Manager project.

Specifies the name of the target variable that was used to train the model.

The target variable value that defines the desired target variable event.

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.

Specifies the class target level of binary, nominal, ordinal, or interval.

The output event probability variable name, when the Model Function property is set to Classification.

The output prediction variable name, when the Model Function property is set to Prediction.

The output classification variable name, when the Model Function property is set to Classification.

The output segmentation variable name, when the Model Function property is set to Segmentation.

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.

Function for models that have target variables that contain binary, categorical, or ordinal values.

DEFAULT_RISK = {Low, Med, High}

Function for segmentation or clustering models.

Clustering models

Specify Any when you import a SAS code model and you want a choice of the model template to use in the Local Files window. When you specify Any, SAS Model Manager lists the available model templates in the Choose a model template list in the Local Files window.

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