Open mbritton-muso opened 3 years ago
This might be related to issue https://github.com/interpretml/interpret/issues/322 even though the error reported is different. The error there suggests using a Pandas dataframe, so that could be one thing to try here. In any case, this is something we need to fix.
I am trying to use the PartialDependence functionality to analyze partial dependence for a data set that includes categorical features (for example, this breast cancer data). When I call PartialDependence(), even if I specify the feature_types parameter, I get an error like
ValueError: could not convert string to float: '20-29'
(see stack trace below). It looks like PartialDependence handles my feature_types parameter but does not modify the data at all? For reference I am generating PDPs for a list of PyCaret models (which have their own automatic feature type detection), and so I'm trying to avoid re-encoding the categorical columns.