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  2. Mean absolute percentage error - Wikipedia

    en.wikipedia.org/wiki/Mean_absolute_percentage_error

    Confusingly, sometimes when people refer to wMAPE they are talking about a different model in which the numerator and denominator of the wMAPE formula above are weighted again by another set of custom weights .

  3. Mean percentage error - Wikipedia

    en.wikipedia.org/wiki/Mean_percentage_error

    Because actual rather than absolute values of the forecast errors are used in the formula, positive and negative forecast errors can offset each other; as a result, the formula can be used as a measure of the bias in the forecasts. A disadvantage of this measure is that it is undefined whenever a single actual value is zero. See also

  4. 68–95–99.7 rule - Wikipedia

    en.wikipedia.org/wiki/68–95–99.7_rule

    In statistics, the 68–95–99.7 rule, also known as the empirical rule, and sometimes abbreviated 3sr, is a shorthand used to remember the percentage of values that lie within an interval estimate in a normal distribution: approximately 68%, 95%, and 99.7% of the values lie within one, two, and three standard deviations of the mean, respectively.

  5. Symmetric mean absolute percentage error - Wikipedia

    en.wikipedia.org/wiki/Symmetric_mean_absolute...

    (200% for the first formula and 100% for the second formula). Provided the data are strictly positive, a better measure of relative accuracy can be obtained based on the log of the accuracy ratio: log( F t / A t ) This measure is easier to analyse statistically, and has valuable symmetry and unbiasedness properties.

  6. Errors and residuals - Wikipedia

    en.wikipedia.org/wiki/Errors_and_residuals

    For example, if the mean height in a population of 21-year-old men is 1.75 meters, and one randomly chosen man is 1.80 meters tall, then the "error" is 0.05 meters; if the randomly chosen man is 1.70 meters tall, then the "error" is −0.05 meters.

  7. Propagation of uncertainty - Wikipedia

    en.wikipedia.org/wiki/Propagation_of_uncertainty

    Propagation of uncertainty. In statistics, propagation of uncertainty (or propagation of error) is the effect of variables ' uncertainties (or errors, more specifically random errors) on the uncertainty of a function based on them. When the variables are the values of experimental measurements they have uncertainties due to measurement ...

  8. Mean squared error - Wikipedia

    en.wikipedia.org/wiki/Mean_squared_error

    Definition and basic properties. The MSE either assesses the quality of a predictor (i.e., a function mapping arbitrary inputs to a sample of values of some random variable), or of an estimator (i.e., a mathematical function mapping a sample of data to an estimate of a parameter of the population from which the data is sampled).

  9. Approximation error - Wikipedia

    en.wikipedia.org/wiki/Approximation_error

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