I would like to build a variety of classification and regression decision trees. My use case focuses on extraction and communication of decision rules. Previously weka was used in my organisation for decision tree learning. What can weka do that Python or Sklearn can't?
I currently use pandas, numpy, scipy, and sk-learn and other libraries for the majority of my workflow.