Get default metrics for binary forecasts
Source:R/class-forecast-binary.R
get_metrics.forecast_binary.Rd
For binary forecasts, the default scoring rules are:
"brier_score" =
brier_score()
"log_score" =
logs_binary()
Usage
# S3 method for class 'forecast_binary'
get_metrics(x, select = NULL, exclude = NULL, ...)
Arguments
- x
A forecast object (a validated data.table with predicted and observed values, see
as_forecast_binary()
).- select
A character vector of scoring rules to select from the list. If
select
isNULL
(the default), all possible scoring rules are returned.- exclude
A character vector of scoring rules to exclude from the list. If
select
is notNULL
, this argument is ignored.- ...
unused
See also
Other get_metrics functions:
get_metrics()
,
get_metrics.forecast_nominal()
,
get_metrics.forecast_point()
,
get_metrics.forecast_quantile()
,
get_metrics.forecast_sample()
,
get_metrics.scores()
Examples
get_metrics(example_binary)
#> $brier_score
#> function (observed, predicted)
#> {
#> assert_input_binary(observed, predicted)
#> observed <- as.numeric(observed) - 1
#> brierscore <- (observed - predicted)^2
#> return(brierscore)
#> }
#> <bytecode: 0x5556c98d2b10>
#> <environment: namespace:scoringutils>
#>
#> $log_score
#> function (observed, predicted)
#> {
#> assert_input_binary(observed, predicted)
#> observed <- as.numeric(observed) - 1
#> logs <- -log(1 - abs(observed - predicted))
#> return(logs)
#> }
#> <bytecode: 0x5556c94edba8>
#> <environment: namespace:scoringutils>
#>
get_metrics(example_binary, select = "brier_score")
#> $brier_score
#> function (observed, predicted)
#> {
#> assert_input_binary(observed, predicted)
#> observed <- as.numeric(observed) - 1
#> brierscore <- (observed - predicted)^2
#> return(brierscore)
#> }
#> <bytecode: 0x5556c98d2b10>
#> <environment: namespace:scoringutils>
#>
get_metrics(example_binary, exclude = "log_score")
#> $brier_score
#> function (observed, predicted)
#> {
#> assert_input_binary(observed, predicted)
#> observed <- as.numeric(observed) - 1
#> brierscore <- (observed - predicted)^2
#> return(brierscore)
#> }
#> <bytecode: 0x5556c98d2b10>
#> <environment: namespace:scoringutils>
#>