analysisnode properties

Last updated: Feb 11, 2025

Analysis node icon The Analysis node evaluates predictive models' ability to generate accurate predictions. Analysis nodes perform various comparisons between predicted values and actual values for one or more model nuggets. They can also compare predictive models to each other.

Example

stream = modeler.script.stream()
node = stream.create("analysis", "My node")
# "Analysis" tab
node.setPropertyValue("coincidence", True)
node.setPropertyValue("performance", True)
node.setPropertyValue("confidence", True)
node.setPropertyValue("threshold", 75)
node.setPropertyValue("improve_accuracy", 3)
node.setPropertyValue("inc_user_measure", True)
# "Define User Measure..."
node.setPropertyValue("user_if", "@TARGET = @PREDICTED")
node.setPropertyValue("user_then", "101")
node.setPropertyValue("user_else", "1")
node.setPropertyValue("user_compute", ["Mean", "Sum"])
node.setPropertyValue("by_fields", ["Drug"])

Table 1. analysisnode properties
`analysisnode` properties	Data type	Property description
`output_mode`	`Screen` `File`	Used to specify target location for output generated from the output node.
`use_output_name`	flag	Specifies whether a custom output name is used.
`output_name`	string	If `use_output_name` is true, specifies the name to use.
`output_format`	`Text` (.txt) `HTML` (.html) `Output` (.cou)	Used to specify the type of output.
`by_fields`	list
`full_filename`	string	If disk, data, or HTML output, the name of the output file.
`coincidence`	flag
`performance`	flag
`evaluation_binary`	flag
`confidence`	flag
`threshold`	number
`improve_accuracy`	number
`field_detection_method`	`Metadata` `Name`	Determines how predicted fields are matched to the original target field. Specify `Metadata` or `Name`.
`inc_user_measure`	flag
`user_if`	expr
`user_then`	expr
`user_else`	expr
`user_compute`	`[Mean Sum Min Max SDev]`
`split_by_partition`	boolean	Whether to separate by partition.

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