Dealing with a MissingMetadataException
estimate methods of a
Estimator fails by returning
nannyml.exceptions.MissingMetadataException: metadata is still missing values for ['predicted_probability_column_name'].
The exception will list the properties it is missing, as shown in the problem statement.
md is the
model metadata object used,
predicted_probability_column_name is the property missing and in your data the predicted probabilities are located
The following snippet should help you prevent the exception by completing the metadata manually:
>>> md.is_complete() # just checking (False, ['predicted_probability_column_name']) >>> md.predicted_probability_column_name = 'model_probas' >>> md.is_complete() (True, )
Any metadata property can be set or updated.