metric_logcosh_error: Computes the logarithm of the hyperbolic cosine of the...

In keras: R Interface to 'Keras'

Computes the logarithm of the hyperbolic cosine of the prediction error

Description

logcosh = log((exp(x) + exp(-x))/2), where x is the error (y_pred - y_true)

Usage

metric_logcosh_error(..., name = "logcosh", dtype = NULL)

Arguments

...	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.

Value

A (subclassed) Metric instance that can be passed directly to compile(metrics = ), or used as a standalone object. See ?Metric for example usage.

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_kullback_leibler_divergence(), metric_mean(), 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_poisson(), metric_precision(), metric_precision_at_recall(), metric_recall(), metric_recall_at_precision(), 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 May 29, 2024, 3:20 a.m.