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Computes the accuracy for binary classification problems where the model returns probabilities. Commonly used when the loss is torch::nn_bce_loss().

Usage

luz_metric_binary_accuracy(threshold = 0.5)

Arguments

threshold

value used to classifiy observations between 0 and 1.

Value

Returns new luz metric.

Examples

if (torch::torch_is_installed()) {
library(torch)
metric <- luz_metric_binary_accuracy(threshold = 0.5)
metric <- metric$new()
metric$update(torch_rand(100), torch::torch_randint(0, 1, size = 100))
metric$compute()
}
#> [1] 0.54