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