ensemblenode properties

The Ensemble node combines two or more model nuggets to obtain more accurate predictions than can be gained from any one model.

Example

# Create and configure an Ensemble node 
# Use this node with the models in demos\streams\pm_binaryclassifier.str
node = stream.create("ensemble", "My node")
node.setPropertyValue("ensemble_target_field", "response")
node.setPropertyValue("filter_individual_model_output", False)
node.setPropertyValue("flag_ensemble_method", "ConfidenceWeightedVoting")
node.setPropertyValue("flag_voting_tie_selection", "HighestConfidence")

Table 1. ensemblenode properties
`ensemblenode` properties	Data type	Property description
`ensemble_target_field`	field	Specifies the target field for all models used in the ensemble.
`filter_individual_model_output`	flag	Specifies whether scoring results from individual models should be suppressed.
`flag_ensemble_method`	`Voting` `ConfidenceWeightedVoting` `RawPropensityWeightedVoting` `AdjustedPropensityWeightedVoting` `HighestConfidence` `AverageRawPropensity` `AverageAdjustedPropensity`	Specifies the method used to determine the ensemble score. This setting applies only if the selected target is a flag field.
`set_ensemble_method`	`Voting` `ConfidenceWeightedVoting` `HighestConfidence`	Specifies the method used to determine the ensemble score. This setting applies only if the selected target is a nominal field.
`flag_voting_tie_selection`	`Random` `HighestConfidence` `RawPropensity` `AdjustedPropensity`	If a voting method is selected, specifies how ties are resolved. This setting applies only if the selected target is a flag 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.
`calculate_standard_error`	flag	If the target field is continuous, a standard error calculation is run by default to calculate the difference between the measured or estimated values and the true values; and to show how close those estimates matched.