def test_accuracy(): """ Tests :func:`fatf.utils.metrics.metrics.accuracy` function. """ acc = fumm.accuracy(CMA) assert acc == pytest.approx(4 / 10, abs=1e-3) acc = fumm.accuracy(CMA_BIN) assert acc == pytest.approx(8 / 26, abs=1e-3)
def accuracy(global_predictions, local_predictions): global_predictions[global_predictions >= 0.5] = 1 global_predictions[global_predictions < 0.5] = 0 local_predictions[local_predictions >= 0.5] = 1 local_predictions[local_predictions < 0.5] = 0 confusion_matrix = fumt.get_confusion_matrix(global_predictions, local_predictions, labels=[0, 1]) accuracy = fummet.accuracy(confusion_matrix) return accuracy
def accuracy_prob(global_predictions, local_predictions, global_proba=True, local_proba=True): if global_proba: global_predictions = np.argmax(global_predictions, axis=1) if local_proba: local_predictions = np.argmax(local_predictions, axis=1) confusion_matrix = fumt.get_confusion_matrix(global_predictions, local_predictions, labels=[0, 1, 2]) accuracy = fummet.accuracy(confusion_matrix) return accuracy