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Description
Currently sklearn logistic classifier only supports predictions.
https://github.com/neilsummers/mleap/blob/master/python/mleap/sklearn/logistic.py
def serialize_to_bundle(self, transformer, path, model_name):
# compile tuples of model attributes to serialize
attributes = list()
attributes.append(('intercept', transformer.intercept_.tolist()[0]))
attributes.append(('coefficients', transformer.coef_.tolist()[0]))
attributes.append(('num_classes', 2)) # TODO: get number of classes from the transformer
# define node inputs and outputs
inputs = [{
"name": transformer.input_features,
"port": "features"
}]
outputs = [{
"name": transformer.prediction_column,
"port": "prediction"
}]
self.serialize(transformer, path, model_name, attributes, inputs, outputs)
Want to be able to access the probabilities from the classifier too. This is already supported in the MLeap logistic model. Just need to add the appropriate outputs. I will create a PR with the change we made to access this for our own production model.