MAPE

class MAPE(mode: str = MetricAggregationMode.per_segment, **kwargs)[source]

Bases: etna.metrics.base.Metric

Mean absolute percentage error metric with multi-segment computation support.

\[MAPE(y\_true, y\_pred) = \frac{1}{n}\cdot\frac{\sum_{i=0}^{n-1}{\mid y\_true_i - y\_pred_i\mid}}{\mid y\_true_i \mid + \epsilon}\]

Notes

You can read more about logic of multi-segment metrics in Metric docs.

Init metric.

Parameters

  • mode ('macro' or 'per-segment') – metrics aggregation mode

  • kwargs – metric’s computation arguments

Inherited-members

Methods

set_params(**params)

Return new object instance with modified parameters.

to_dict()

Collect all information about etna object in dict.

Attributes

greater_is_better

Whether higher metric value is better.

name

Name of the metric for representation.
property greater_is_better: bool

Whether higher metric value is better.