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

  Type → metrics.base.RegressionMetric

  A regression metric.

• agg_func

  Type → 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

list[float]: The current performance.

update

Update the metric at each step along the horizon.

Parameters

• y_true — 'list[Number]'
• y_pred — 'list[Number]'

Returns

ForecastingMetric: self