metric_true_negatives
Calculates the number of true negatives
Description
Calculates the number of true negatives
Usage
metric_true_negatives(..., thresholds = NULL, name = NULL, dtype = NULL)
Arguments
Arguments | Description |
---|---|
… | Passed on to the underlying metric. Used for forwards and backwards compatibility. |
thresholds | (Optional) Defaults to 0.5. A float value or a list of float threshold values in [0, 1] . A threshold is compared with prediction values to determine the truth value of predictions (i.e., above the threshold is true , below is false ). One metric value is generated for each threshold value. |
name | (Optional) string name of the metric instance. |
dtype | (Optional) data type of the metric result. |
Details
If sample_weight
is given, calculates the sum of the weights of true negatives. This metric creates one local variable, accumulator
that is used to keep track of the number of true negatives. If sample_weight
is NULL
, weights default to 1. Use sample_weight
of 0 to mask values.
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_wrapper()
, 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_positives()