tf.keras.losses.SquaredHinge

Computes the squared hinge loss between y_true & y_pred.

Inherits From: Loss

tf.keras.losses.SquaredHinge(
    reduction='sum_over_batch_size', name='squared_hinge'
)

Formula:

loss = square(maximum(1 - y_true * y_pred, 0))

y_true values are expected to be -1 or 1. If binary (0 or 1) labels are provided we will convert them to -1 or 1.

Args
reduction	Type of reduction to apply to the loss. In almost all cases this should be "sum_over_batch_size". Supported options are "sum", "sum_over_batch_size" or None.
name	Optional name for the loss instance.

Methods

call

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call(
    y_true, y_pred
)

from_config

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@classmethod
from_config(
    config
)

get_config

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get_config()

__call__

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__call__(
    y_true, y_pred, sample_weight=None
)

Call self as a function.