Dear all,
In the sklearn.metrics module, the precision_recall_fscore_support and
precision_score have different default value for the "average" parameter, which
seems a bit counterintuitive -- but I did not go deep into the code. Is this
really the intended behavior ?
def precision_score(y_true, y_pred, labels=None, pos_label=1,
average='weighted')
def precision_recall_fscore_support(y_true, y_pred, beta=1.0, labels=None,
pos_label=1, average=None)
Best ,
Bertrand
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