Wraps a stateless metric function with the Mean metric
metric_mean_wrapper(..., fn, name = NULL, dtype = NULL)
A (subclassed) Metric
instance that can be passed directly to
compile(metrics = )
, or used as a standalone object. See ?Metric
for
example usage.
named arguments to pass on to fn
.
The metric function to wrap, with signature fn(y_true, y_pred, ...)
.
(Optional) string name of the metric instance.
(Optional) data type of the metric result.
You could use this class to quickly build a mean metric from a function. The
function needs to have the signature fn(y_true, y_pred)
and return a
per-sample loss array. MeanMetricWrapper$result()
will return
the average metric value across all samples seen so far.
For example:
accuracy <- function(y_true, y_pred)
k_cast(y_true == y_pred, 'float32')accuracy_metric <- metric_mean_wrapper(fn = accuracy)
model %>% compile(..., metrics=accuracy_metric)
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()
,
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()