Default metrics and scoring rules for binary forecasts

Helper function that returns a named list of default scoring rules suitable for binary forecasts.

The default scoring rules are:

"brier_score" = brier_score()
"log_score" = logs_binary()

Usage

metrics_binary(select = NULL, exclude = NULL)

Arguments

select: A character vector of scoring rules to select from the list. If select is NULL (the default), all possible scoring rules are returned.
exclude: A character vector of scoring rules to exclude from the list. If select is not NULL, this argument is ignored.

Value

A list of scoring functions.

Input format

Examples

metrics_binary()
#> $brier_score
#> function (observed, predicted) 
#> {
#>     assert_input_binary(observed, predicted)
#>     observed <- as.numeric(observed) - 1
#>     brierscore <- (observed - predicted)^2
#>     return(brierscore)
#> }
#> <bytecode: 0x55cdb839db10>
#> <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: 0x55cdb7e90c88>
#> <environment: namespace:scoringutils>
#> 
metrics_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: 0x55cdb839db10>
#> <environment: namespace:scoringutils>
#> 
metrics_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: 0x55cdb839db10>
#> <environment: namespace:scoringutils>
#>