tf.keras.metrics.top_k_categorical_accuracy
Computes how often targets are in the top K predictions.
tf.keras.metrics.top_k_categorical_accuracy(
y_true, y_pred, k=5
)
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)
| 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. |