Model persistence in Scikit-Learn?

Question

I am trying to save and load scikit-learn model but facing issues when the save and load are happening on different python versions. Here what I have tried:

1. Using pickle to save a model in python3 and deserialize in python2.This works for some of the models like LR,SVM but it fails for KNN.

    >>> pickle.load(open("inPy3.pkl", 'rb')) #KNN model ValueError: non-string names in Numpy dtype unpickling

2. Also, I tried to serialize and deserialize in json using jsonpickle but getting the following error.

    data = jsonpickle.encode(lr) #lr = logisticRegression Model jsonpickle.decode(data) AttributeError: 'dict' object has no attribute '__name__'

Also, I want to know if there is some utility which I can use to serialize and deserialize scikit-learn model objects to human readable format (json,xml,protobuf etc).

Answer 1

Instead of pickling whole models, you can extract and store their coefficients. Then load coefficients and init models with them.

Related to sklearn upgrade question . Similar approach will be valid for python versions.