View source on GitHub |
Calculates how often predictions matches binary labels.
tf.keras.metrics.binary_accuracy( y_true, y_pred, threshold=0.5 )
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] |
© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/keras/metrics/binary_accuracy