torchtraining.functional.metrics.classification.binary module

torchtraining.functional.metrics.classification.binary.accuracy(output: torch.Tensor, target: torch.Tensor, threshold: float = 0.0, reduction: Callable[torch.Tensor, torch.Tensor] = <built-in method mean of type object>) → torch.Tensor

See torchtrainingnal.metrics.classification.binary.Accuracy for details.

torchtraining.functional.metrics.classification.binary.balanced_accuracy(output: torch.Tensor, target: torch.Tensor, threshold: float = 0.0) → torch.Tensor

See torchtrainingnal.metrics.classification.binary.BalancedAccuracy for details.

torchtraining.functional.metrics.classification.binary.confusion_matrix(output: torch.Tensor, target: torch.Tensor, threshold: float = 0.0, reduction: Callable[torch.Tensor, torch.Tensor] = <built-in method sum of type object>) → torch.Tensor

See torchtrainingnal.metrics.classification.binary.ConfusionMatrix for details.

torchtraining.functional.metrics.classification.binary.critical_success_index(output: torch.Tensor, target: torch.Tensor, threshold: float = 0.0) → torch.Tensor

See torchtrainingnal.metrics.classification.binary.CriticalSuccessIndex for details.

torchtraining.functional.metrics.classification.binary.f1(output: torch.Tensor, target: torch.Tensor, threshold: float = 0.0) → torch.Tensor

See torchtrainingnal.metrics.classification.binary.F1 for details.

torchtraining.functional.metrics.classification.binary.f_beta(output: torch.Tensor, target: torch.Tensor, beta: float, threshold: float = 0.0) → torch.Tensor

See torchtrainingnal.metrics.classification.binary.FBeta for details.

torchtraining.functional.metrics.classification.binary.false_discovery_rate(output: torch.Tensor, target: torch.Tensor, threshold: float = 0.0) → torch.Tensor

See torchtrainingnal.metrics.classification.binary.FalseDiscoveryRate for details.

torchtraining.functional.metrics.classification.binary.false_negative(output: torch.Tensor, target: torch.Tensor, threshold: float = 0.0, reduction: Callable[torch.Tensor, torch.Tensor] = <built-in method sum of type object>) → torch.Tensor

See torchtrainingnal.metrics.classification.binary.FalseNegative for details.

torchtraining.functional.metrics.classification.binary.false_negative_rate(output: torch.Tensor, target: torch.Tensor, threshold: float = 0.0) → torch.Tensor

See torchtrainingnal.metrics.classification.binary.FalseNegativeRate for details.

torchtraining.functional.metrics.classification.binary.false_omission_rate(output: torch.Tensor, target: torch.Tensor, threshold: float = 0.0) → torch.Tensor

See torchtrainingnal.metrics.classification.binary.FalseOmissionRate for details.

torchtraining.functional.metrics.classification.binary.false_positive(output: torch.Tensor, target: torch.Tensor, threshold: float = 0.0, reduction: Callable[torch.Tensor, torch.Tensor] = <built-in method sum of type object>) → torch.Tensor

See torchtrainingnal.metrics.classification.binary.FalsePositive for details.

torchtraining.functional.metrics.classification.binary.false_positive_rate(output: torch.Tensor, target: torch.Tensor, threshold: float = 0.0) → torch.Tensor

See torchtrainingnal.metrics.classification.binary.FalsePositiveRate for details.

torchtraining.functional.metrics.classification.binary.jaccard(output: torch.Tensor, target: torch.Tensor, threshold: float = 0.0, reduction: Callable[torch.Tensor, torch.Tensor] = <built-in method mean of type object>) → torch.Tensor

See torchtrainingnal.metrics.classification.binary.Jaccard for details.

torchtraining.functional.metrics.classification.binary.matthews_correlation_coefficient(output: torch.Tensor, target: torch.Tensor, threshold: float = 0.0) → torch.Tensor

See torchtrainingnal.metrics.classification.binary.MatthewsCorrelationCoefficient for details.

torchtraining.functional.metrics.classification.binary.negative_predictive_value(output: torch.Tensor, target: torch.Tensor, threshold: float = 0.0) → torch.Tensor

See torchtrainingnal.metrics.classification.binary.NegativePredictiveValue for details.

torchtraining.functional.metrics.classification.binary.precision(output: torch.Tensor, target: torch.Tensor, threshold: float = 0.0) → torch.Tensor

See torchtrainingnal.metrics.classification.binary.Precision for details.

torchtraining.functional.metrics.classification.binary.recall(output: torch.Tensor, target: torch.Tensor, threshold: float = 0.0) → torch.Tensor

See torchtrainingnal.metrics.classification.binary.Recall for details.

torchtraining.functional.metrics.classification.binary.specificity(output: torch.Tensor, target: torch.Tensor, threshold: float = 0.0) → torch.Tensor

See torchtrainingnal.metrics.classification.binary.Specificity for details.

torchtraining.functional.metrics.classification.binary.true_negative(output: torch.Tensor, target: torch.Tensor, threshold: float = 0.0, reduction: Callable[torch.Tensor, torch.Tensor] = <built-in method sum of type object>) → torch.Tensor

See torchtrainingnal.metrics.classification.binary.TrueNegative for details.

torchtraining.functional.metrics.classification.binary.true_positive(output: torch.Tensor, target: torch.Tensor, threshold: float = 0.0, reduction: Callable[torch.Tensor, torch.Tensor] = <built-in method sum of type object>) → torch.Tensor

See torchtrainingnal.metrics.classification.binary.TruePositive for details.