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Computes how often targets are in the top K
predictions.
tf.keras.metrics.top_k_categorical_accuracy( y_true, y_pred, k=5 )
y_true = [[0, 0, 1], [0, 1, 0]] y_pred = [[0.1, 0.9, 0.8], [0.05, 0.95, 0]] m = tf.keras.metrics.top_k_categorical_accuracy(y_true, y_pred, k=3) assert m.shape == (2,) m.numpy() array([1., 1.], dtype=float32)
Args | |
---|---|
y_true | The ground truth values. |
y_pred | The prediction values. |
k | (Optional) Number of top elements to look at for computing accuracy. Defaults to 5. |
Returns | |
---|---|
Top K categorical accuracy value. |
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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/top_k_categorical_accuracy