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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. Evaluation of binary classifiers - Wikipedia

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

    This has a useful interpretation – as an odds ratio – and is prevalence-independent. Likelihood ratio is generally considered to be prevalence-independent and is easily interpreted as the multiplier to turn prior probabilities into posterior probabilities. An F-score is a combination of the precision and the recall, providing

  5. Binary classification - Wikipedia

    en.wikipedia.org/wiki/Binary_classification

    The F-score combines precision and recall into one number via a choice of weighing, most simply equal weighing, as the balanced F-score . Some metrics come from regression coefficients : the markedness and the informedness , and their geometric mean , the Matthews correlation coefficient .

  6. Accuracy paradox - Wikipedia

    en.wikipedia.org/wiki/Accuracy_paradox

    Even though the accuracy is ⁠ 10 + 999000 / 1000000 ⁠ ≈ 99.9%, 990 out of the 1000 positive predictions are incorrect. 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 ...

  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. Cal vs. UNLV: Predictions, odds, how to watch Art of ... - AOL

    www.aol.com/cal-vs-unlv-predictions-odds...

    California scores 26.1 per game but allows 22.2 per game.” Cal vs. UNLV: Art of Sport Bowl odds The California Golden Bears are favorites to defeat the UNLV Rebels , according to BetMGM NCAA odds .

  9. Youden's J statistic - Wikipedia

    en.wikipedia.org/wiki/Youden's_J_statistic

    When the true prevalences for the two positive variables are equal as assumed in Fleiss kappa and F-score, that is the number of positive predictions matches the number of positive classes in the dichotomous (two class) case, the different kappa and correlation measure collapse to identity with Youden's J, and recall, precision and F-score are ...