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Custom metric function

Source: R/metrics.R
custom_metric.Rd

Custom metric function

Usage

custom_metric(name, metric_fn)

Arguments

name

name used to show training progress output

metric_fn

An R function with signature function(y_true, y_pred) that accepts tensors.

Value

A callable function with a __name__ attribute.

Details

You can provide an arbitrary R function as a custom metric. Note that the y_true and y_pred parameters are tensors, so computations on them should use op_* tensor functions.

Use the custom_metric() function to define a custom metric. Note that a name ('mean_pred') is provided for the custom metric function: this name is used within training progress output.

If you want to save and load a model with custom metrics, you should also call register_keras_serializable(), or specify the metric in the call the load_model(). For example: load_model("my_model.keras", c('mean_pred' = metric_mean_pred)).

Alternatively, you can wrap all of your code in a call to with_custom_object_scope() which will allow you to refer to the metric by name just like you do with built in keras metrics.

Alternative ways of supplying custom metrics:

  • custom_metric(): Arbitrary R function.

  • metric_mean_wrapper(): Wrap an arbitrary R function in a Metric instance.

  • Create a custom Metric() subclass.

See also

Other metrics:
Metric()
metric_auc()
metric_binary_accuracy()
metric_binary_crossentropy()
metric_binary_focal_crossentropy()
metric_binary_iou()
metric_categorical_accuracy()
metric_categorical_crossentropy()
metric_categorical_focal_crossentropy()
metric_categorical_hinge()
metric_cosine_similarity()
metric_f1_score()
metric_false_negatives()
metric_false_positives()
metric_fbeta_score()
metric_hinge()
metric_huber()
metric_iou()
metric_kl_divergence()
metric_log_cosh()
metric_log_cosh_error()
metric_mean()
metric_mean_absolute_error()
metric_mean_absolute_percentage_error()
metric_mean_iou()
metric_mean_squared_error()
metric_mean_squared_logarithmic_error()
metric_mean_wrapper()
metric_one_hot_iou()
metric_one_hot_mean_iou()
metric_poisson()
metric_precision()
metric_precision_at_recall()
metric_r2_score()
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()