metric_mean | R Documentation |
Computes the (weighted) mean of the given values
metric_mean(..., name = "mean", dtype = NULL)
... |
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. |
For example, if values is c(1, 3, 5, 7)
then the mean is 4.
If the weights were specified as c(1, 1, 0, 0)
then the mean would be 2.
This metric creates two variables, total
and count
that are used to
compute the average of values
. This average is ultimately returned as mean
which is an idempotent operation that simply divides total
by count
.
If sample_weight
is NULL
, weights default to 1.
Use sample_weight
of 0 to mask values.
A (subclassed) Metric
instance that can be passed directly to
compile(metrics = )
, or used as a standalone object. See ?Metric
for
example usage.
Unlike most other metrics, this only takes a single tensor as input to update state.
Example usage with compile()
:
model$add_metric(metric_mean(name='mean_1')(outputs)) model %>% compile(optimizer='sgd', loss='mse')
Example standalone usage:
m <- metric_mean() m$update_state(c(1, 3, 5, 7)) m$result() m$reset_state() m$update_state(c(1, 3, 5, 7), sample_weight=c(1, 1, 0, 0)) m$result() as.numeric(m$result())
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_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()
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