tf.keras.metrics.top_k_categorical_accuracy

Computes how often targets are in the top K predictions.

Standalone usage:

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)

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.

Top K categorical accuracy value.