HorizonAggMetric

Same as HorizonMetric, but aggregates the result based on an provided function.

This allows, for instance, to measure the average performance of a forecasting model along the horizon.

Parameters

• metric ('metrics.base.RegressionMetric')

  A regression metric.

• agg_func ('typing.Callable[[list[float]], float]')

  A function that takes as input a list of floats and outputs a single float. You may want to min, max, as well as statistics.mean and statistics.median.

Examples

This is used internally by the time_series.evaluate function when you pass an agg_func.

>>> import statistics
>>> from river import datasets
>>> from river import metrics
>>> from river import time_series

>>> metric = time_series.evaluate(
...     dataset=datasets.AirlinePassengers(),
...     model=time_series.HoltWinters(alpha=0.1),
...     metric=metrics.MAE(),
...     agg_func=statistics.mean,
...     horizon=4
... )

>>> metric
mean(MAE): 42.901748

Methods

get

Return the current performance along the horizon.

Returns

typing.List[float]: The current performance.

update

Update the metric at each step along the horizon.

Parameters

• y_true ('typing.List[Number]')
• y_pred ('typing.List[Number]')

Returns

'ForecastingMetric': self