loss_squared_hinge: Computes the squared hinge loss between 'y_true' & 'y_pred'.

In rstudio/keras: R Interface to 'Keras'

Computes the squared hinge loss between y_true & y_pred.

Description

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.

Usage

loss_squared_hinge(
  y_true,
  y_pred,
  ...,
  reduction = "sum_over_batch_size",
  name = "squared_hinge"
)

Arguments

y_true	The ground truth values. 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 with shape = ⁠[batch_size, d0, .. dN]⁠.
y_pred	The predicted values with shape = ⁠[batch_size, d0, .. dN]⁠.
...	For forward/backward compatability.
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 NULL.
name	Optional name for the loss instance.

Value

Squared hinge loss values with shape = ⁠[batch_size, d0, .. dN-1]⁠.

Examples

y_true <- array(sample(c(-1,1), 6, replace = TRUE), dim = c(2, 3))
y_pred <- random_uniform(c(2, 3))
loss <- loss_squared_hinge(y_true, y_pred)

See Also

• https://keras.io/api/losses/hinge_losses#squaredhinge-class

Other losses:
Loss()
loss_binary_crossentropy()
loss_binary_focal_crossentropy()
loss_categorical_crossentropy()
loss_categorical_focal_crossentropy()
loss_categorical_hinge()
loss_cosine_similarity()
loss_ctc()
loss_dice()
loss_hinge()
loss_huber()
loss_kl_divergence()
loss_log_cosh()
loss_mean_absolute_error()
loss_mean_absolute_percentage_error()
loss_mean_squared_error()
loss_mean_squared_logarithmic_error()
loss_poisson()
loss_sparse_categorical_crossentropy()
loss_tversky()
metric_binary_crossentropy()
metric_binary_focal_crossentropy()
metric_categorical_crossentropy()
metric_categorical_focal_crossentropy()
metric_categorical_hinge()
metric_hinge()
metric_huber()
metric_kl_divergence()
metric_log_cosh()
metric_mean_absolute_error()
metric_mean_absolute_percentage_error()
metric_mean_squared_error()
metric_mean_squared_logarithmic_error()
metric_poisson()
metric_sparse_categorical_crossentropy()
metric_squared_hinge()

rstudio/keras documentation built on April 27, 2024, 10:11 p.m.