model.save() is not built for sklearn models as opposed to keras/tensorflow models. You might want to save them as you would do with other python objects as follows:
- Save model using pickle
# save the model to disk
filename = 'finalized_model.sav'
pickle.dump(model, open(filename, 'wb'))
# some time later...
# load the model from disk
loaded_model = pickle.load(open(filename, 'rb'))
result = loaded_model.score(X_test, Y_test)
- Save model using joblib:
# save the model to disk
filename = 'finalized_model.sav'
joblib.dump(model, filename)
# some time later...
# load the model from disk
loaded_model = joblib.load(filename)
result = loaded_model.score(X_test, Y_test)
If you are interested, this article has these codes with examples. Also check the link to the SO question that might already answer what you are looking for