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Computes accuracy for binary classification problems where the model return logits. Commonly used together with torch::nn_bce_with_logits_loss().

Usage

luz_metric_binary_accuracy_with_logits(threshold = 0.5)

Arguments

threshold

value used to classifiy observations between 0 and 1.

Value

Returns new luz metric.

Details

Probabilities are generated using torch::nnf_sigmoid() and threshold is used to classify between 0 or 1.

Examples

if (torch::torch_is_installed()) {
library(torch)
metric <- luz_metric_binary_accuracy_with_logits(threshold = 0.5)
metric <- metric$new()
metric$update(torch_randn(100), torch::torch_randint(0, 1, size = 100))
metric$compute()
}
#> [1] 0.46