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Results tagged with precision-recall
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user 69409
P&R are a way to measure the relevance of set of retrieved instances. Precision is the % of correct instances out of all instances retrieved. Relevance is the % of true instances retrieved. The harmonic mean of P&R is the F1-score. P&R are used in data mining to evaluate classifiers.
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How to compute precision/recall for multiclass-multilabel classification?
From Ozgur et al (2005) it is possible to see that you should compute Precision and Recall following the normal expressions, but instead of averaging over total N instances in your dataset, you should …
