| metric_logcosh_error {keras} | R Documentation |
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()