Precision & Recall

Wikipedia: Precision and Recall See Information Retrieval Confusion Matrix

Value of 1 is only possible for Recall, not for Precision.

… relevant is what the user likes … recommended what the RS predicts

Precision

Precision

Precision (Accuracy) is a measure for how many useful items were recommended. $Precision=\frac{relevantrecomm.}{allrecomm.}=\frac{TP}{TP+FP}$

→ The portion that you have suggested “correctly”. → Better for Find Good Item Tasks

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Recall

Recall

Recall/Sensitivity (Completeness) is the fraction of relevant instances over all relevant items for that user. $Recall=\frac{relevantrecomm.}{relevantitems}=\frac{TP}{TP+FN}$ → 4 correctly suggested out of 5, all of which are true

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