enow.com Web Search

Search results

  1. Results from the WOW.Com Content Network
  2. Precision and recall - Wikipedia

    en.wikipedia.org/wiki/Precision_and_recall

    In a classification task, the precision for a class is the number of true positives (i.e. the number of items correctly labelled as belonging to the positive class) divided by the total number of elements labelled as belonging to the positive class (i.e. the sum of true positives and false positives, which are items incorrectly labelled as belonging to the class).

  3. 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 ]

  4. 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 ...

  5. File:Precision and recall.pdf - Wikipedia

    en.wikipedia.org/wiki/File:Precision_and_recall.pdf

    You are free: to share – to copy, distribute and transmit the work; to remix – to adapt the work; Under the following conditions: attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made.

  6. Evaluation of binary classifiers - Wikipedia

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

    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 ...

  7. Accuracy paradox - Wikipedia

    en.wikipedia.org/wiki/Accuracy_paradox

    The precision of ⁠ 10 / 10 + 990 ⁠ = 1% reveals its poor performance. As the classes are so unbalanced, a better metric is the F1 score = ⁠ 2 × 0.01 × 1 / 0.01 + 1 ⁠ ≈ 2% (the recall being ⁠ 10 + 0 / 10 ⁠ = 1).

  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. Thesaurus (information retrieval) - Wikipedia

    en.wikipedia.org/wiki/Thesaurus_(information...

    In information retrieval, a thesaurus can be used as a form of controlled vocabulary to aid in the indexing of appropriate metadata for information bearing entities. A thesaurus helps with expressing the manifestations of a concept in a prescribed way, to aid in improving precision and recall. This means that the semantic conceptual expressions ...