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Saving Random Forest

I want to save and load a fitted Random Forest Classifier, but I get an error.

forest = RandomForestClassifier(n_estimators = 100, max_features = mf_val)
forest = forest.fit(L1[0:100], L2[0:100])
joblib.dump(forest, 'screening_forest/screening_forest.pkl')
forest2 = joblib.load('screening_forest/screening_forest.pkl')

The error is:

  File "C:\Users\mkolarek\Documents\other\TrackerResultAnalysis\ScreeningClassif
ier\ScreeningClassifier.py", line 67, in <module>
    forest2 = joblib.load('screening_forest/screening_forest.pkl')
  File "C:\Python27\lib\site-packages\sklearn\externals\joblib\numpy_pickle.py",
 line 425, in load
    obj = unpickler.load()
  File "C:\Python27\lib\pickle.py", line 858, in load
    dispatch[key](self)
  File "C:\Python27\lib\site-packages\sklearn\externals\joblib\numpy_pickle.py",
 line 285, in load_build
    Unpickler.load_build(self)
  File "C:\Python27\lib\pickle.py", line 1217, in load_build
    setstate(state)
  File "_tree.pyx", line 2280, in sklearn.tree._tree.Tree.__setstate__ (sklearn\
tree\_tree.c:18350)
ValueError: Did not recognise loaded array layout
Press any key to continue . . .

Do I have to initialize forest2 or something?

like image 252
mkolarek Avatar asked Dec 17 '14 11:12

mkolarek


1 Answers

I solved it with cPickle instead:

with open('screening_forest/screening_forest.pickle', 'wb') as f:
    cPickle.dump(forest, f)

with open('screening_forest/screening_forest.pickle', 'rb') as f:
    forest2 = cPickle.load(f)

but a joblib solution could be useful as well.

like image 181
mkolarek Avatar answered Oct 18 '22 17:10

mkolarek