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  2. Mean absolute percentage error - Wikipedia

    en.wikipedia.org/wiki/Mean_absolute_percentage_error

    It is a variant of MAPE in which the mean absolute percent errors is treated as a weighted arithmetic mean. Most commonly the absolute percent errors are weighted by the actuals (e.g. in case of sales forecasting, errors are weighted by sales volume).. Effectively, this overcomes the 'infinite error' issue. Its formula is:

  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. Symmetric mean absolute percentage error - Wikipedia

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

    This is illustrated by the following example by applying the second SMAPE formula: Over-forecasting: A t = 100 and F t = 110 give SMAPE = 4.76% Under-forecasting: A t = 100 and F t = 90 give SMAPE = 5.26%.

  5. Relative change - Wikipedia

    en.wikipedia.org/wiki/Relative_change

    A percentage change is a way to express a change in a variable. It represents the relative change between the old value and the new one. For example, if a house is worth $100,000 today and the year after its value goes up to $110,000, the percentage change of its value can be expressed as

  6. Approximation error - Wikipedia

    en.wikipedia.org/wiki/Approximation_error

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  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. 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.