metric_log_cosh_error {keras3}

Computes the logarithm of the hyperbolic cosine of the prediction error.

Description

Formula:

error <- y_pred - y_true
logcosh <- mean(log((exp(error) + exp(-error))/2), axis=-1)

Usage

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

Arguments

...

For forward/backward compatability.

name

(Optional) string name of the metric instance.

dtype

(Optional) data type of the metric result.

Value

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

Examples

Standalone usage:

m <- metric_log_cosh_error()
m$update_state(rbind(c(0, 1), c(0, 0)), rbind(c(1, 1), c(0, 0)))
m$result()

## tf.Tensor(0.108445205, shape=(), dtype=float32)

m$reset_state()
m$update_state(rbind(c(0, 1), c(0, 0)), rbind(c(1, 1), c(0, 0)),
               sample_weight = c(1, 0))
m$result()

## tf.Tensor(0.21689041, shape=(), dtype=float32)

Usage with compile() API:

model %>% compile(optimizer = 'sgd',
                  loss = 'mse',
                  metrics = list(metric_log_cosh_error()))

See Also

• https://keras.io/api/metrics/regression_metrics#logcosherror-class

Other regression metrics:
metric_cosine_similarity()
metric_mean_absolute_error()
metric_mean_absolute_percentage_error()
metric_mean_squared_error()
metric_mean_squared_logarithmic_error()
metric_r2_score()
metric_root_mean_squared_error()

Other metrics:
Metric()
custom_metric()
metric_auc()
metric_binary_accuracy()
metric_binary_crossentropy()
metric_binary_focal_crossentropy()
metric_binary_iou()
metric_categorical_accuracy()
metric_categorical_crossentropy()
metric_categorical_focal_crossentropy()
metric_categorical_hinge()
metric_cosine_similarity()
metric_f1_score()
metric_false_negatives()
metric_false_positives()
metric_fbeta_score()
metric_hinge()
metric_huber()
metric_iou()
metric_kl_divergence()
metric_log_cosh()
metric_mean()
metric_mean_absolute_error()
metric_mean_absolute_percentage_error()
metric_mean_iou()
metric_mean_squared_error()
metric_mean_squared_logarithmic_error()
metric_mean_wrapper()
metric_one_hot_iou()
metric_one_hot_mean_iou()
metric_poisson()
metric_precision()
metric_precision_at_recall()
metric_r2_score()
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()