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How can I include predefined entities in my concept model compilation?

You can include predefined entities by setting the 'enablePredefined' parameter to TRUE. By default, this parameter is set to FALSE.

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On: compileConcept

table

specifies the settings for an input table. Long form: table={name="table-name"} Shortcut form: table="table-name" The castable value can be one or more of the following: caslib: specifies the caslib for the input table that you want to use with the action. By default, the active caslib is used. Specify a value only if you need to access a table from a different caslib. computedOnDemand: when set to True, creates the computed variables when the table is loaded instead of when the action begins. Alias: compOnDemand Default: FALSE computedVars: specifies the names of the computed variables to create. Specify an expression for each variable in the computedVarsProgram parameter. If you do not specify this parameter, then all variables from computedVarsProgram are automatically included. Alias: compVars format: specifies the format to apply to the variable. formattedLength: specifies the length of the format field plus the length of the format precision. label: specifies the descriptive label for the variable. name: specifies the name for the variable. nfd: specifies the length of the format precision. nfl: specifies the length of the format field. computedVarsProgram: specifies an expression for each computed variable that you include in the computedVars parameter. Alias: compPgm dataSourceOptions: specifies data source options. Aliases: options, dataSource importOptions: specifies the settings for reading a table from a data source. Alias: import For more information about specifying the importOptions parameter, see the common importOptions parameter. name: specifies the name of the input table. singlePass: when set to True, does not create a transient table on the server. Setting this parameter to True can be efficient, but the data might not have stable ordering upon repeated runs. Default: FALSE vars: specifies the variables to use in the action. format: specifies the format to apply to the variable. formattedLength: specifies the length of the format field plus the length of the format precision. label: specifies the descriptive label for the variable. name: specifies the name for the variable. nfd: specifies the length of the format precision. nfl: specifies the length of the format field. where: specifies an expression for subsetting the input data. whereTable: specifies an input table that contains rows to use as a WHERE filter. If the vars parameter is not specified, then all the variable names that are common to the input table and the filtering table are used to find matching rows. If the where parameter for the input table and this parameter are specified, then this filtering table is applied first. casLib: specifies the caslib for the filter table. By default, the active caslib is used. dataSourceOptions: specifies data source options. Aliases: options, dataSource For more information about specifying the dataSourceOptions parameter, see the common dataSourceOptions parameter. importOptions: specifies the settings for reading a table from a data source. Alias: import For more information about specifying the importOptions parameter, see the common importOptions parameter. name: specifies the name of the filter table. vars: specifies the variable names to use from the filter table. format: specifies the format to apply to the variable. formattedLength: specifies the length of the format field plus the length of the format precision. label: specifies the descriptive label for the variable. name: specifies the name for the variable. nfd: specifies the length of the format precision. nfl: specifies the length of the format field. where: specifies an expression for subsetting the data from the filter table.

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On: forestTrain

What is tolerance parameter for?

Specifies the tolerance for the iterative robust univariate statistics. Default is 1E-05.

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On: histogram

What is the primary function of the mbcScore action?

The mbcScore action produces clustering weights using a previously stored model.

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On: mbcScore

How is the output SAS score code specified using the 'casOut' subparameter within the 'code' parameter?

The 'casOut' subparameter, used within the 'code' parameter, specifies the output table where the generated SAS score code will be stored. It can take several additional subparameters such as 'caslib', 'compress', 'name', 'promote', 'replace', etc., to define the output table's properties.

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On: forestCode