- FactorTable
- [Optional] Specify the name for the output table that contains the result. The result is based on either CategoricalColumns or Randomization; therefore, you must also specify either CategoricalColumns or Randomization ('true').
- FeatureColumns
- Specify the names of the InputTable columns that contain the variables to use as predictors (independent variables) in the model.
- CategoricalColumns
- [Optional] Specify the names of the InputTable columns that contain categorical variables, and which of their categories to use in the model.
- Randomization
- [Optional] Specify whether to randomize the InputTable data. If you use this argument, you must also specify the FactorTable argument.
- ResponseColumn
- Specify the name of the InputTable column that contains the responses.
- Family
- [Optional] Specify the distribution exponential family.
- Alpha
- [Optional] Specify the mixing parameter for penalty computation (see the following table). The alpha must be in [0, 1]. If alpha is in (0,1), it represents α in the elastic net regularization formula in Generalized Linear Model Functions.
alpha Regularization Type Parameter Description 0 Ridge ½ (0,1) Elastic net 1 LASSO - Lambda
- [Optional] Specify the parameter that controls the magnitude of the regularization term. A value of zero disables regularization.
- StopThreshold
- [Optional] Specify the convergence threshold. The threshold must be a nonnegative DOUBLE PRECISION value.
- MaxIterNum
- [Optional] Specify the maximum number of iterations over the data. The parameter max_iterations must be a positive INTEGER value in the range [1, 100000].