plot_cross_validation_metric: Plot a performance metric vs. forecast horizon from cross...
In prophet: Automatic Forecasting Procedure

Description Usage Arguments Details Value

This uses fbprophet.diagnostics.performance_metrics to compute the metrics. Valid values of metric are 'mse', 'rmse', 'mae', 'mape', and 'coverage'.

1	plot_cross_validation_metric(df_cv, metric, rolling_window = 0.1)

`df_cv`	The output from fbprophet.diagnostics.cross_validation.
`metric`	Metric name, one of 'mse', 'rmse', 'mae', 'mape', 'coverage'.
`rolling_window`	Proportion of data to use for rolling average of metric. In [0, 1]. Defaults to 0.1.

rolling_window is the proportion of data included in the rolling window of aggregation. The default value of 0.1 means 10 aggregation for computing the metric.

As a concrete example, if metric='mse', then this plot will show the squared error for each cross validation prediction, along with the MSE averaged over rolling windows of 10

A ggplot2 plot.

prophet documentation built on March 30, 2021, 5:05 p.m.