tf.keras.metrics.SparseTopKCategoricalAccuracy

TensorFlow 1 version

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Computes how often integer targets are in the top K predictions.

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Main aliases

tf.metrics.sparse_top_k_categorical_accuracy

Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.keras.metrics.sparse_top_k_categorical_accuracy

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.

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tf.keras / metrics / metrics.SparseTopKCategoricalAccuracy

View aliases

Standalone usage:

Args

Returns