metric_sum
Computes the (weighted) sum of the given values
Description
Computes the (weighted) sum of the given values
Usage
metric_sum(..., name = NULL, 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. |
Details
For example, if values is c(1, 3, 5, 7)
then the sum is 16. If the weights were specified as c(1, 1, 0, 0)
then the sum would be 4. This metric creates one variable, total
, that is used to compute the sum of values
. This is ultimately returned as sum
. If sample_weight
is NULL
, weights default to 1. Use sample_weight
of 0 to mask values.
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_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_top_k_categorical_accuracy()
, metric_true_negatives()
, metric_true_positives()