metric_mean_wrapper: Wraps a stateless metric function with the Mean metric

In keras: R Interface to 'Keras'

Wraps a stateless metric function with the Mean metric

Description

Wraps a stateless metric function with the Mean metric

Usage

metric_mean_wrapper(..., fn, name = NULL, dtype = NULL)

Arguments

...	named arguments to pass on to fn.
fn	The metric function to wrap, with signature fn(y_true, y_pred, ...).
name	(Optional) string name of the metric instance.
dtype	(Optional) data type of the metric result.

Details

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)

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(), 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()

keras documentation built on Aug. 16, 2023, 1:07 a.m.