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  2. Accuracy and precision - Wikipedia

    en.wikipedia.org/wiki/Accuracy_and_precision

    Accuracy is sometimes also viewed as a micro metric, to underline that it tends to be greatly affected by the particular class prevalence in a dataset and the classifier's biases. [14] Furthermore, it is also called top-1 accuracy to distinguish it from top-5 accuracy, common in convolutional neural network evaluation. To evaluate top-5 ...

  3. Uncertainty - Wikipedia

    en.wikipedia.org/wiki/Uncertainty

    There is a difference between uncertainty and variability. Uncertainty is quantified by a probability distribution which depends upon knowledge about the likelihood of what the single, true value of the uncertain quantity is. Variability is quantified by a distribution of frequencies of multiple instances of the quantity, derived from observed ...

  4. Uncertainty quantification - Wikipedia

    en.wikipedia.org/wiki/Uncertainty_quantification

    Uncertainty quantification (UQ) is the science of quantitative characterization and estimation of uncertainties in both computational and real world applications. It tries to determine how likely certain outcomes are if some aspects of the system are not exactly known.

  5. Measurement uncertainty - Wikipedia

    en.wikipedia.org/wiki/Measurement_uncertainty

    Relative uncertainty is the measurement uncertainty relative to the magnitude of a particular single choice for the value for the measured quantity, when this choice is nonzero. This particular single choice is usually called the measured value, which may be optimal in some well-defined sense (e.g., a mean, median, or mode). Thus, the relative ...

  6. Observational error - Wikipedia

    en.wikipedia.org/wiki/Observational_error

    The Performance Test Standard PTC 19.1-2005 "Test Uncertainty", published by the American Society of Mechanical Engineers (ASME), discusses systematic and random errors in considerable detail. In fact, it conceptualizes its basic uncertainty categories in these terms.

  7. Calibration (statistics) - Wikipedia

    en.wikipedia.org/wiki/Calibration_(statistics)

    There are two main uses of the term calibration in statistics that denote special types of statistical inference problems. Calibration can mean a reverse process to regression, where instead of a future dependent variable being predicted from known explanatory variables, a known observation of the dependent variables is used to predict a corresponding explanatory variable; [1]

  8. Sensitivity analysis - Wikipedia

    en.wikipedia.org/wiki/Sensitivity_analysis

    The uncertainty on the output is ... The difference between the unconditional and conditional output ... it is useful to check the accuracy of the ...

  9. Standard error - Wikipedia

    en.wikipedia.org/wiki/Standard_error

    1.2.1 Accuracy of the ... Standard errors provide simple measures of uncertainty in a value and are often used because: ... the difference between the finite- and ...