Type SquaredHinge
Namespace tensorflow.keras.losses
Parent LossFunctionWrapper
Interfaces ISquaredHinge
Computes the squared hinge loss between `y_true` and `y_pred`. `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. Usage:
Usage with the `compile` API:
Show Example
sh = tf.keras.losses.SquaredHinge()
loss = sh([-1., 1., 1.], [0.6, -0.7, -0.5]) # loss = (max(0, 1 - y_true * y_pred))^2 = [1.6^2 + 1.7^2 + 1.5^2] / 3 print('Loss: ', loss.numpy()) # Loss: 2.566666