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Which model selection criterion can be used in the mbcFit action to find the best model?

The 'criterion' parameter lets you specify the model selection criterion. Available options are 'AIC' (Akaike Information Criterion), 'AICC' (Corrected Akaike Information Criterion), 'BIC' (Bayesian Information Criterion), and 'LOGL' (Log-Likelihood).

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On: mbcFit

How can I save the state of my trained model for later use?

You can use the 'saveState' parameter to specify an output table where the model's state, including its weights, will be saved. This allows you to resume training later or use the model for scoring with the 'annScore' action.

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On: annTrain

includeMissing

by default, observations with missing values are included. When set to False, observations with missing values for the variables used in the tree model are ignored when scoring. Default: TRUE

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On: forestTrain

Which parameter is required to specify the copula simulation input table?

The `copulaSample` parameter is required. It specifies the name of the input table that contains the copula simulation in uniform margins.

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On: ecm

What is the "groupBy" action?

The "groupBy" action builds BY groups in terms of the variable value combinations given the variables in the variable list. It is part of the Simple Analytics Action Set.

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On: groupBy