analysisnode properties

Analysis node iconThe 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.


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.