It seems like these functions can be used to compute precision and
recall for something like a search engine, where you get a set of
results for a query, but not for classifier evaluation. scikit-learn
has precision, recall and F1 for classification, if that's what you're
looking for. http://scikit-learn.org/stable/modules/classes.html#classification-metrics
2012/2/19 Rami Al-Rfou' <rmy...@gmail.com>:
> I am trying to figure out how to use precision and recall methods in nltk.It seems like these functions can be used to compute precision and
> There is no examples in the module to explain usage.
>
> While accuracy method accepts lists of gold and test lists to compute
> accuracy, precision and recall methods accept sets of values.
recall for something like a search engine, where you get a set of
results for a query, but not for classifier evaluation.
scikit-learn
has precision, recall and F1 for classification, if that's what you're
looking for. http://scikit-learn.org/stable/modules/classes.html#classification-metrics
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Never mind my previous comment. J. Perkins feeds sets of indices to
the precision and recall functions. The only difficulty is then that
the measures have to be computed per class and averaging is left to
the user. I hadn't thought of that possibility.