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  2. Numeric precision in Microsoft Excel - Wikipedia

    en.wikipedia.org/wiki/Numeric_precision_in...

    Excel's storage of numbers in binary format also affects its accuracy. [3] To illustrate, the lower figure tabulates the simple addition 1 + x − 1 for several values of x. All the values of x begin at the 15 th decimal, so Excel must take them into account. Before calculating the sum 1 + x, Excel first approximates x as a binary number

  3. Symmetric mean absolute percentage error - Wikipedia

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

    The earliest reference to a similar formula appears to be Armstrong (1985, p. 348), where it is called "adjusted MAPE" and is defined without the absolute values in the denominator. It was later discussed, modified, and re-proposed by Flores (1986).

  4. Circular error probable - Wikipedia

    en.wikipedia.org/wiki/Circular_error_probable

    The concept of CEP also plays a role when measuring the accuracy of a position obtained by a navigation system, ... is given by the following formula: (, ...

  5. Mean absolute percentage error - Wikipedia

    en.wikipedia.org/wiki/Mean_absolute_percentage_error

    This little-known but serious issue can be overcome by using an accuracy measure based on the logarithm of the accuracy ratio (the ratio of the predicted to actual value), given by ⁡ (). This approach leads to superior statistical properties and also leads to predictions which can be interpreted in terms of the geometric mean.

  6. Positive and negative predictive values - Wikipedia

    en.wikipedia.org/wiki/Positive_and_negative...

    The positive predictive value (PPV), or precision, is defined as = + = where a "true positive" is the event that the test makes a positive prediction, and the subject has a positive result under the gold standard, and a "false positive" is the event that the test makes a positive prediction, and the subject has a negative result under the gold standard.

  7. Mean absolute scaled error - Wikipedia

    en.wikipedia.org/wiki/Mean_absolute_scaled_error

    It was proposed in 2005 by statistician Rob J. Hyndman and Professor of Decision Sciences Anne B. Koehler, who described it as a "generally applicable measurement of forecast accuracy without the problems seen in the other measurements."

  8. Root mean square deviation - Wikipedia

    en.wikipedia.org/wiki/Root_mean_square_deviation

    The RMSD serves to aggregate the magnitudes of the errors in predictions for various data points into a single measure of predictive power. RMSD is a measure of accuracy, to compare forecasting errors of different models for a particular dataset and not between datasets, as it is scale-dependent. [1]

  9. Nash–Sutcliffe model efficiency coefficient - Wikipedia

    en.wikipedia.org/wiki/Nash–Sutcliffe_model...

    This indicator can be used to describe the predictive accuracy of other models as long as there is observed data to compare the model results to. For example, Nash–Sutcliffe efficiency has been reported in scientific literature for model simulations of discharge; water quality constituents such as sediment , nitrogen, and phosphorus loading ...