tf.keras.metrics.sparse_categorical_accuracy
Calculates how often predictions matches integer labels.
tf.keras.metrics.sparse_categorical_accuracy(
y_true, y_pred
)
Standalone usage:
y_true = [2, 1]
y_pred = [[0.1, 0.9, 0.8], [0.05, 0.95, 0]]
m = tf.keras.metrics.sparse_categorical_accuracy(y_true, y_pred)
assert m.shape == (2,)
m.numpy()
array([0., 1.], dtype=float32)
You can provide logits of classes as y_pred, since argmax of logits and probabilities are same.
| Args | |
|---|---|
y_true |
Integer ground truth values. |
y_pred |
The prediction values. |
| Returns | |
|---|---|
| Sparse categorical accuracy values. |
© 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/r2.4/api_docs/python/tf/keras/metrics/sparse_categorical_accuracy