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Last updated: Feb 11, 2025
The Evaluation node helps to evaluate and compare predictive
models. The evaluation chart shows how well models predict particular outcomes. It sorts records
based on the predicted value and confidence of the prediction. It splits the records into groups of
equal size (quantiles) and then plots the value of the business criterion for each
quantile from highest to lowest. Multiple models are shown as separate lines in the plot.
Example
stream = modeler.script.stream()
typenode = stream.findByID("id42KW3MSA94B")
node = stream.create("evaluation", "My node")
stream.link(typenode, node)
# "Plot" tab
node.setPropertyValue("chart_type", "Gains")
node.setPropertyValue("cumulative", False)
node.setPropertyValue("field_detection_method", "Name")
node.setPropertyValue("inc_baseline", True)
node.setPropertyValue("n_tile", "Deciles")
node.setPropertyValue("style", "Point")
node.setPropertyValue("plot_score_fields", True)
node.setPropertyValue("score_fields", ["Na", "K", "Age"])
node.setPropertyValue("use_fixed_cost", True)
node.setPropertyValue("cost_value", 5.0)
node.setPropertyValue("target_field", "Drug")
node.setPropertyValue("cost_field", "Na")
node.setPropertyValue("use_fixed_revenue", True)
node.setPropertyValue("revenue_value", 30.0)
node.setPropertyValue("revenue_field", "Age")
node.setPropertyValue("use_fixed_weight", True)
node.setPropertyValue("weight_value", 2.0)
node.setPropertyValue("weight_field", "K")
properties |
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[field1 ... fieldN] | |
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field | |
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flag | |
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boolean | If a partition field is used to split records into training, test, and validation samples, use this option to display a separate evaluation chart for each partition. |
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boolean | Enables profit criteria. |
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boolean | Displays grid lines. |
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