tf.keras.metrics.sparse_top_k_categorical_accuracy

TensorFlow 1 version View source on GitHub

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)

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.

Sparse top K categorical accuracy value.