Good Afternoon,
I'm trying to pickle a class that contains a reference to a
GridSearchCV object and it is failing due to an instancemethod type. I
was under the impression that scikit-learn objects should be
picklable, is this correct? If so, would it be appropriate for me to
raise an issue?
Information about the Exception is included below.
Thanks,
Martin
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
/tmp/<ipython-input-7-687becba8c7c> in <module>()
----> 1 cPickle.dump(gs, te)
/opt/epd-7.2/lib/python2.7/copy_reg.pyc in _reduce_ex(self, proto)
68 else:
69 if base is self.__class__:
---> 70 raise TypeError, "can't pickle %s objects" % base.__name__
71 state = base(self)
72 args = (self.__class__, base, state)
TypeError: can't pickle instancemethod objects
print GridSearchCV:
GridSearchCV(cv=sklearn.cross_validation.StratifiedKFold(labels=[ 1.
1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.
1. 1. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
0. 0. 0. 0. 0. 0.], k=10),
estimator=LinearSVC(C=1.0, dual=True, fit_intercept=True,
intercept_scaling=1,
loss='l2', multi_class=False, penalty='l2', tol=0.0001),
fit_params={}, iid=True, loss_func=None, n_jobs=4,
param_grid={'C': [1, 10, 100, 1000, 10000, 100000]},
pre_dispatch='2*n_jobs', refit=True, score_func=None, verbose=1)
The method causing the problem is LinearSVC.predict:
> /opt/epd-7.2/lib/python2.7/copy_reg.py(70)_reduce_ex()
69 if base is self.__class__:
---> 70 raise TypeError, "can't pickle %s objects" % base.__name__
71 state = base(self)
ipdb> self
<bound method LinearSVC.predict of LinearSVC(C=1, dual=True,
fit_intercept=True, intercept_scaling=1, loss='l2',
multi_class=False, penalty='l2', tol=0.0001)>
------------------------------------------------------------------------------
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