loss_tversky: Computes the Tversky loss value between 'y_true' and...

In rstudio/keras: R Interface to 'Keras'

Computes the Tversky loss value between y_true and y_pred.

Description

This loss function is weighted by the alpha and beta coefficients that penalize false positives and false negatives.

With alpha=0.5 and beta=0.5, the loss value becomes equivalent to Dice Loss.

This loss function is weighted by the alpha and beta coefficients that penalize false positives and false negatives.

With alpha=0.5 and beta=0.5, the loss value becomes equivalent to Dice Loss.

Usage

loss_tversky(
  y_true,
  y_pred,
  ...,
  alpha = 0.5,
  beta = 0.5,
  reduction = "sum_over_batch_size",
  name = "tversky",
  dtype = NULL
)

Arguments

y_true	tensor of true targets.
y_pred	tensor of predicted targets.
...	For forward/backward compatability.
alpha	The coefficient controlling incidence of false positives. Defaults to 0.5.
beta	The coefficient controlling incidence of false negatives. Defaults to 0.5.
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. (string)
dtype	The dtype of the loss's computations. Defaults to NULL, which means using config_floatx(). config_floatx() is a "float32" unless set to different value (via config_set_floatx()).

Value

Tversky loss value.

Reference

• Salehi et al., 2017

See Also

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_squared_hinge()
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 July 8, 2024, 3:07 p.m.