metric_mean_wrapper
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
Arguments | Description |
---|---|
… | 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()