metric_kullback_leibler_divergence: Computes Kullback-Leibler divergence

In keras: R Interface to 'Keras'

Computes Kullback-Leibler divergence

Description

Computes Kullback-Leibler divergence

Usage

metric_kullback_leibler_divergence(
  y_true,
  y_pred,
  ...,
  name = "kullback_leibler_divergence",
  dtype = NULL
)

Arguments

y_true	Tensor of true targets.
y_pred	Tensor of predicted targets.
...	Passed on to the underlying metric. Used for forwards and backwards compatibility.
name	(Optional) string name of the metric instance.
dtype	(Optional) data type of the metric result.

Details

metric = y_true * log(y_true / y_pred)

See: https://en.wikipedia.org/wiki/Kullback%E2%80%93Leibler_divergence

Value

If y_true and y_pred are missing, a (subclassed) Metric instance is returned. The Metric object can be passed directly to compile(metrics = ) or used as a standalone object. See ?Metric for example usage.

Alternatively, if called with y_true and y_pred arguments, then the computed case-wise values for the mini-batch are returned directly.

See Also

Other metrics: custom_metric(), metric_accuracy(), metric_auc(), metric_binary_accuracy(), metric_binary_crossentropy(), metric_categorical_accuracy(), metric_categorical_crossentropy(), metric_categorical_hinge(), metric_cosine_similarity(), metric_false_negatives(), metric_false_positives(), metric_hinge(), metric_logcosh_error(), metric_mean_absolute_error(), metric_mean_absolute_percentage_error(), metric_mean_iou(), metric_mean_relative_error(), metric_mean_squared_error(), metric_mean_squared_logarithmic_error(), metric_mean_tensor(), metric_mean_wrapper(), metric_mean(), metric_poisson(), metric_precision_at_recall(), metric_precision(), metric_recall_at_precision(), metric_recall(), metric_root_mean_squared_error(), metric_sensitivity_at_specificity(), metric_sparse_categorical_accuracy(), metric_sparse_categorical_crossentropy(), metric_sparse_top_k_categorical_accuracy(), metric_specificity_at_sensitivity(), metric_squared_hinge(), metric_sum(), metric_top_k_categorical_accuracy(), metric_true_negatives(), metric_true_positives()

keras documentation built on Aug. 16, 2023, 1:07 a.m.