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What is the purpose of the crfTrain action?

The crfTrain action is used to train a Conditional Random Fields (CRF) model for sequence labeling tasks.

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On: crfTrain

outputTableOptions={outputTableOptions}

specifies options for result tables. You can specify which result tables the server returns and how group-by results are handled. Alias tblOpts The outputTableOptions value can be one or more of the following: forceTableReturn=TRUE | FALSE when set to True, result tables are returned to the client even if the output is also saved as an output table. Default FALSE tableNames={"string-1" } specifies the names of result tables to generate. By default, all result tables are returned. Alias outputTables

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On: impute

What does the 'inputRegEx' parameter do?

The 'inputRegEx' parameter specifies a list of regular expressions, one for each variable in the inputs list.

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On: groupByInfo

What is the primary purpose of the factmac action?

The factmac action is designed to learn a factorization machine model.

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On: factmac

model.model.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. The casinvardesc value can be one or more of the following: format, formattedLength, label, name (required), nfd, nfl.

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On: IdentifySpeakers