tfa.metrics.hamming_distance

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Computes hamming distance.

tfa.metrics.hamming_distance(
    actuals: tfa.types.TensorLike,
    predictions: tfa.types.TensorLike
) -> tf.Tensor

Hamming distance is for comparing two binary strings. It is the number of bit positions in which two bits are different.

Args
actuals	actual target value.
predictions	predicted value.

Returns
hamming distance: float.

Usage:

y_true = np.array([1, 1, 0, 0, 1, 0, 1, 0, 0, 1], dtype=np.int32)
y_pred = np.array([1, 0, 0, 0, 1, 0, 0, 1, 0, 1], dtype=np.int32)
hamming_distance(y_true, y_pred).numpy()
0.3