metric_logcosh_error
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
Arguments | Description |
---|---|
… | 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_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()