tf.keras.metrics.sparse_top_k_categorical_accuracy
Computes how often integer targets are in the top K predictions.
tf.keras.metrics.sparse_top_k_categorical_accuracy(
y_true, y_pred, k=5
)
Standalone usage:
y_true = [2, 1]
y_pred = [[0.1, 0.9, 0.8], [0.05, 0.95, 0]]
m = tf.keras.metrics.sparse_top_k_categorical_accuracy(
y_true, y_pred, k=3)
assert m.shape == (2,)
m.numpy()
array([1., 1.], dtype=float32)
| Args | |
|---|---|
y_true |
tensor of true targets. |
y_pred |
tensor of predicted targets. |
k |
(Optional) Number of top elements to look at for computing accuracy. Defaults to 5. |
| Returns | |
|---|---|
| Sparse top K categorical accuracy value. |
© 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_top_k_categorical_accuracy