Calculates how often predictions match binary labels.
tf.keras.metrics.binary_accuracy(
y_true, y_pred, threshold=0.5
)
Standalone usage:
y_true = [[1], [1], [0], [0]]
y_pred = [[1], [1], [0], [0]]
m = tf.keras.metrics.binary_accuracy(y_true, y_pred)
assert m.shape == (4,)
m.numpy()
array([1., 1., 1., 1.], dtype=float32)
Args |
|---|
y_true
|
Ground truth values. shape = [batch_size, d0, .. dN].
|
y_pred
|
The predicted values. shape = [batch_size, d0, .. dN].
|
threshold
|
(Optional) Float representing the threshold for deciding
whether prediction values are 1 or 0.
|
Returns |
|---|
Binary accuracy values. shape = [batch_size, d0, .. dN-1]
|
View source on GitHub