ensemblenode properties
Last updated: Feb 11, 2025
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
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")
properties |
Data type | Property description |
---|---|---|
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field | Specifies the target field for all models used in the ensemble. |
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flag | Specifies whether scoring results from individual models should be suppressed. |
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|
Specifies the method used to determine the ensemble score. This setting applies only if the selected target is a flag field. |
|
|
Specifies the method used to determine the ensemble score. This setting applies only if the selected target is a nominal field. |
|
|
If a voting method is selected, specifies how ties are resolved. This setting applies only if the selected target is a flag field. |
|
|
If a voting method is selected, specifies how ties are resolved. This setting applies only if the selected target is a nominal field. |
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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. |
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