numpy

NumPy implementation of Metrics.

Functions

numpy_accuracy	Compute top-1 classification accuracy for NumPy arrays.
numpy_auc	Compute area under a curve using the trapezoid rule.
numpy_average_precision_score	Compute average precision for NumPy arrays.
numpy_categorical_accuracy	Compute accuracy for a categorical distribution via its class probabilities.
numpy_categorical_classwise_ece	Compute the classwise ECE for a categorical distribution via its class probabilities.
numpy_categorical_expected_calibration_error	Compute the confidence ECE for a categorical distribution via its class probabilities.
numpy_classwise_ece	Compute the classwise expected calibration error for NumPy arrays.
numpy_expected_calibration_error	Compute the confidence expected calibration error for NumPy arrays.
numpy_false_negative_rate	Compute the false negative rate for NumPy arrays.
numpy_false_positive_rate	Compute the false positive rate for NumPy arrays.
numpy_precision_recall_curve	Compute precision-recall curve along the last axis.
numpy_roc_auc_score	Compute area under the ROC curve for NumPy arrays.
numpy_roc_curve	Compute ROC curve along the last axis.