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Metric

MeanArctangentAbsolutePercentageError

API referenceSource
Multivariate

Mean Arctangent Absolute Percentage Error (MAAPE).

Quickstart

python
from sktime.performance_metrics.forecasting import MeanArctangentAbsolutePercentageError

estimator = MeanArctangentAbsolutePercentageError(multioutput='uniform_average', multilevel='uniform_average', relative_to='y_true', eps=None, by_index=False)

Parameters(5)

multioutput{‘raw_values’, ‘uniform_average’}, default=’uniform_average’
Defines aggregating of multiple output values.
multilevel{‘raw_values’, ‘uniform_average’}, default=’uniform_average’
Defines aggregating of multiple hierarchical levels.
relative_to{“y_true”, “y_pred”}, default=”y_true”
Determines the denominator of the percentage error.
epsfloat, default=None
Numerical epsilon used in denominator to avoid division by zero.
by_indexbool, default=False
If True, return the metric value at each time point. If False, return the aggregate metric value.

References

  1. Kim, S., & Kim, H. (2016). “A new metric of absolute percentage error for intermittent demand forecasts”. International Journal of Systems Science.