Wraps a stateless metric function with the Mean metric
metric_mean_wrapper(..., fn, name = NULL, dtype = NULL)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.
A (subclassed) Metric instance that can be passed directly to
compile(metrics = ), or used as a standalone object. See ?Metric for
example usage.
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()