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Mape Absolute Vs Signed Actual Policy

Calculate one absolute prediction-error ratio with an explicit absolute or signed actual-denominator policy.

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Description

Calculate one absolute prediction error under a chosen actual-value denominator convention.

Prediction metrics depend on the observation definition, reference forecast, denominator sign and aggregation. A single error contribution differs from a mean score or normalized skill measure. Interval midpoints, squared probability errors and seasonal-denominator labels must retain the exact convention before models are compared.

Calculate one absolute prediction error under a chosen actual-value denominator convention.

When to use this tool

Use Mape Absolute Vs Signed Actual Policy when you already have actual, predicted, absoluteActualDenominator and need to calculate one absolute prediction error under a chosen actual-value denominator convention.

How to use the tool and how it works

  1. Enter actual, predicted, absoluteActualDenominator. Use the units and conventions below.
  2. Run the tool. Correct any format, range, or cross-field input error before interpreting the output.
  3. Read errorFraction. Use the output convention below.

Require actual!=0; return abs(predicted-actual)/abs(actual), or divide by signed actual when absoluteActualDenominator=false.1

Input fieldMeaning and unitsAccepted input
actualActualRequired. Finite number.
predictedPredictedRequired. Finite number.
absoluteActualDenominatorAbsolute Actual DenominatorRequired. Boolean.
Output fieldInterpretationReturned shape
errorFractionabs(predicted-actual) divided by abs(actual) or signed actual. One fraction, not a mean or percentage number.Required. Finite number.
json
{
  "input": {
    "actual": -10,
    "predicted": -8,
    "absoluteActualDenominator": true
  },
  "output": {
    "errorFraction": 0.2
  }
}

Limitations and assumptions

  • This returns one fraction, not a mean or percentage number. A negative actual with the signed-denominator policy gives a negative result; no forecasting quality threshold is selected.
  • Inputs must satisfy both the field types and the cross-field conditions above. Invalid input causes an error; a successful false flag or documented placeholder is a different result.
  • Numeric calculations use binary floating point unless exact decimal-integer arithmetic is explicitly stated. No hidden measurement tolerance or decimal rounding is added; nonfinite or out-of-contract results are rejected. Numeric signed-zero results are exported as zero.

Alternative or Complementary methods

Calculate the complete documented metric over the intended observations and reference baseline. Review missing/zero actuals, aggregation weights and outcome coding; one contribution or source label does not establish overall forecasting quality.

References

  1. Calculation and input contract: metrics/mape-absolute-vs-signed-actual-policy — tool.io

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