powered by
For binary forecasts, the default scoring rules are:
"brier_score" = brier_score()
brier_score()
"log_score" = logs_binary()
logs_binary()
# S3 method for forecast_binary get_metrics(x, select = NULL, exclude = NULL, ...)
A list of scoring functions.
A forecast object (a validated data.table with predicted and observed values, see as_forecast_binary()).
as_forecast_binary()
A character vector of scoring rules to select from the list. If select is NULL (the default), all possible scoring rules are returned.
select
NULL
A character vector of scoring rules to exclude from the list. If select is not NULL, this argument is ignored.
unused
Overview of required input format for binary and point forecasts
Other get_metrics functions: get_metrics(), get_metrics.forecast_nominal(), get_metrics.forecast_ordinal(), get_metrics.forecast_point(), get_metrics.forecast_quantile(), get_metrics.forecast_sample(), get_metrics.scores()
get_metrics()
get_metrics.forecast_nominal()
get_metrics.forecast_ordinal()
get_metrics.forecast_point()
get_metrics.forecast_quantile()
get_metrics.forecast_sample()
get_metrics.scores()
get_metrics(example_binary) get_metrics(example_binary, select = "brier_score") get_metrics(example_binary, exclude = "log_score")
Run the code above in your browser using DataLab