tfa.metrics.hamming_loss_fn

Computes hamming loss.

tfa.metrics.hamming_loss_fn(
    y_true: tfa.types.TensorLike,
    y_pred: tfa.types.TensorLike,
    threshold: Union[FloatTensorLike, None],
    mode: str
) -> tf.Tensor

Hamming loss is the fraction of wrong labels to the total number of labels.

In multi-class classification, hamming loss is calculated as the hamming distance between y_true and y_pred. In multi-label classification, hamming loss penalizes only the individual labels.

y_true actual target value.
y_pred predicted target value.
threshold Elements of y_pred greater than threshold are converted to be 1, and the rest 0. If threshold is None, the argmax is converted to 1, and the rest 0.
mode multi-class or multi-label.

hamming loss: float.