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I am new to the open source InterpretML Python package and I want to know if it is essential converting categorical data to numerical ones in order to use any glass/black box thank you!

baddy
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  • What does the documentation say? Does the package accept non-numerical data types for the categories? What happened when you tried it? – Prune Mar 11 '20 at 15:59

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For training EBMs (Explainable Boosting Machines), which are glassbox models, you do not need to convert categorical data to numeric. EBM can accept Pandas dataframes containing a mixture of types (numeric and strings representing categoricals), and will handle conversions implicitly.

For other methods in InterpretML, including blackbox methods, you will need to handle conversions yourself at this time (through a technique like One Hot Encoding).

Harsha Nori
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  • So at this point if I will train my data using the two methods (Black & Glass) you advice me to convert categorical data so I can compare them (Black & Glass) or no matter? – baddy Mar 15 '20 at 10:39