applyautoclassifiernode Properties

Auto Classifier modeling nodes can be used to generate an Auto Classifier model nugget. The scripting name of this model nugget is applyautoclassifiernode.For more information on scripting the modeling node itself, autoclassifiernode properties

Table 1. applyautoclassifiernode properties
`applyautoclassifiernode` Properties	Values	Property description
`flag_ensemble_method`	`Voting` `EvaluationWeightedVoting` `ConfidenceWeightedVoting` `RawPropensityWeightedVoting` `HighestConfidence` `AverageRawPropensity`	Specifies the method used to determine the ensemble score. This setting applies only if the selected target is a flag field.
`flag_evaluation_selection`	`Accuracy` `AUC_ROC`	This option is for flag target only, to decide which evaluation measure is chosen for evaluation-weighted voting.
`filter_individual_model_output`	flag	Specifies whether scoring results from individual models should be suppressed.
`is_ensemble_update`	flag	Enables continuous auto machine learning mode, which adds new component models into an existing auto model set instead of replacing the existing auto model, and re-evaluates measures of existing component models using newly available data.
`is_auto_ensemble_weights_reevaluation`	flag	Enables automatic model weights reevaluation.
`use_accumulated_factor`	flag	Accumulated factor is used to compute accumulated measures.
`accumulated_factor`	number (double)	Max value is `0.99`, and min value is `0.85`.
`use_accumulated_reducing`	flag	Performs model reducing based on accumulated limit during model refresh.
`accumulated_reducing_limit`	number (double)	Max value is `0.7`, and min value is `0.1`.
`use_accumulated_weighted_evaluation`	flag	Accumulated evaluation measure is used for voting when the evaluation-weighted voting method is selected for the ensemble method.
`flag_voting_tie_selection`	`Random` `HighestConfidence` `RawPropensity`	If a voting method is selected, specifies how ties are resolved. This setting applies only if the selected target is a flag field.
`set_ensemble_method`	`Voting` `EvaluationWeightedVoting` `ConfidenceWeightedVoting` `HighestConfidence`	Specifies the method used to determine the ensemble score. This setting applies only if the selected target is a set field.
`set_voting_tie_selection`	`Random` `HighestConfidence`	If a voting method is selected, specifies how ties are resolved. This setting applies only if the selected target is a nominal field.