Using if statement as a model in orange

I am seeking to evaluate logistic regression against a rule-based (nested if-else statements) classification in Orange.

The steps I've taken to investigate this are as follows:

  1. I could not identify any widgets that would implement this. The closest I could find was the interactive tree from version 2.7, but this widget seems to have been discontinued.
  2. I've attempted to generate the results I'm looking for by editing the in_data object produced by creating a tree, sending the results to the Test and Score widget, and then editing the results in Python Script to create an out_data object. However, the out_data object I produce won't work within the confusion matrix.

Is there an easier way to implement this rule-based criterion in Orange? If not, are there some other steps I can use to implement it within the Python script?

Thank you,

Topic orange3 anaconda orange python

Category Data Science


Feature Constructor will help.

{val} if {condition} else {val} if {condition} else {val}

https://orange3.readthedocs.io/projects/orange-visual-programming/en/latest/widgets/data/featureconstructor.html

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