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  2. Precision and recall - Wikipedia

    en.wikipedia.org/wiki/Precision_and_recall

    A precision-recall curve plots precision as a function of recall; usually precision will decrease as the recall increases. Alternatively, values for one measure can be compared for a fixed level at the other measure (e.g. precision at a recall level of 0.75) or both are combined into a single measure.

  3. F-score - Wikipedia

    en.wikipedia.org/wiki/F-score

    Precision and recall. In statistical analysis of binary classification and information retrieval systems, the F-score or F-measure is a measure of predictive performance. It is calculated from the precision and recall of the test, where the precision is the number of true positive results divided by the number of all samples predicted to be positive, including those not identified correctly ...

  4. Receiver operating characteristic - Wikipedia

    en.wikipedia.org/wiki/Receiver_operating...

    The ROC curve plots parametrically () versus () with as the varying parameter. For example, imagine that the blood protein levels in diseased people and healthy people are normally distributed with means of 2 g/dL and 1 g/dL respectively. A medical test might measure the level of a certain protein in a blood sample and classify any number above ...

  5. Sensitivity and specificity - Wikipedia

    en.wikipedia.org/wiki/Sensitivity_and_specificity

    In information retrieval, the positive predictive value is called precision, and sensitivity is called recall. Unlike the Specificity vs Sensitivity tradeoff, these measures are both independent of the number of true negatives, which is generally unknown and much larger than the actual numbers of relevant and retrieved documents.

  6. Evaluation of binary classifiers - Wikipedia

    en.wikipedia.org/wiki/Evaluation_of_binary...

    For example, in medicine sensitivity and specificity are often used, while in computer science precision and recall are preferred. An important distinction is between metrics that are independent of the prevalence or skew (how often each class occurs in the population), and metrics that depend on the prevalence – both types are useful, but ...

  7. Evaluation measures (information retrieval) - Wikipedia

    en.wikipedia.org/wiki/Evaluation_measures...

    By computing a precision and recall at every position in the ranked sequence of documents, one can plot a precision-recall curve, plotting precision () as a function of recall . Average precision computes the average value of p ( r ) {\displaystyle p(r)} over the interval from r = 0 {\displaystyle r=0} to r = 1 {\displaystyle r=1} : [ 7 ]

  8. Accuracy and precision - Wikipedia

    en.wikipedia.org/wiki/Accuracy_and_precision

    Commonly used metrics include the notions of precision and recall. In this context, precision is defined as the fraction of documents correctly retrieved compared to the documents retrieved (true positives divided by true positives plus false positives), using a set of ground truth relevant results selected by humans. Recall is defined as the ...

  9. File:Precision and Recall Curve.png - Wikipedia

    en.wikipedia.org/wiki/File:Precision_and_Recall...

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