luz_metric_binary_accuracy {luz} | R Documentation |
Binary accuracy
Description
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.
See Also
Other luz_metrics:
luz_metric_accuracy()
,
luz_metric_binary_accuracy_with_logits()
,
luz_metric_binary_auroc()
,
luz_metric_mae()
,
luz_metric_mse()
,
luz_metric_multiclass_auroc()
,
luz_metric_rmse()
,
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()
}
[Package luz version 0.4.0 Index]