combust/mleap

Logistic Regression prediction probabilities

Open

#464 ouverte le 22 déc. 2018

Voir sur GitHub
 (0 commentaires) (0 réactions) (0 assignés)Scala (312 forks)batch import
help wantedwaiting for input

Métriques du dépôt

Stars
 (1 461 stars)
Métriques de merge PR
 (Aucune PR mergée en 30 j)

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.

Guide contributeur