So in attempt to get multiple score metrics from the cross_val_score(), I
made a scorer from metrics.precision_recall_
fscore_support(), and when using it, it throws an error:
File
"/usr/local/lib64/python2.7/site-packages/sklearn/cross_validation.py",
line 1174, in cross_val_score
for train, test in cv)
File
"/usr/local/lib64/python2.7/site-packages/sklearn/externals/joblib/parallel.py",
line 514, in __call__
self.dispatch(function, args, kwargs)
File
"/usr/local/lib64/python2.7/site-packages/sklearn/externals/joblib/parallel.py",
line 311, in dispatch
job = ImmediateApply(func, args, kwargs)
File
"/usr/local/lib64/python2.7/site-packages/sklearn/externals/joblib/parallel.py",
line 135, in __init__
self.results = func(*args, **kwargs)
File
"/usr/local/lib64/python2.7/site-packages/sklearn/cross_validation.py",
line 1084, in _cross_val_score
" instead." % (str(score), type(score)))
ValueError: scoring must return a number, got (array([ 0.96153846,
0.94318182]), array([ 0.83333333, 0.98809524]), array([ 0.89285714,
0.96511628]), array([30, 84])) (<type 'tuple'>) instead.
I realize this is something in the code that I can't modify in my script,
but I was wondering if there's a specific reason why the scoring must
return only one number? From the array in the error message, it doesn't
seem to have any problem calculating multiple metrics for a
cross-validation fold, just storing them.If the return function was just
tweaked to accept multiple values, that would give the scoring function a
lot more functionality.
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