Scikits-Learn RandomForrest trained on 64bit pytho

问题:

I train a RandomForestRegressor model on 64bit python. I pickle the object. When trying to unpickle the object on 32bit python I get the following error:

'ValueError: Buffer dtype mismatch, expected 'SIZE_t' but got 'long long''

I really have no idea how to fix this, so any help would be hugely appreciated.

Edit: more detail

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "c:\python27\lib\pickle.py", line 1378, in load
    return Unpickler(file).load()
  File "c:\python27\lib\pickle.py", line 858, in load
    dispatch[key](self)
  File "c:\python27\lib\pickle.py", line 1133, in load_reduce
    value = func(*args)
  File "_tree.pyx", line 1282, in sklearn.tree._tree.Tree.__cinit__ (sklearn\tre
e\_tree.c:10389)

回答1:

This occurs because the random forest code uses different types for indices on 32-bit and 64-bit machines. This can, unfortunately, only be fixed by overhauling the random forests code. Since several scikit-learn devs are working on that anyway, I put it on the todo list.

For now, the training and testing machines need to have the same pointer size.