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ensemblenode properties
ensemblenode properties
Last updated: Feb 12, 2025
ensemblenode properties

Ensemble node iconThe 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 
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.