metric_true_positives
Calculates the number of true positives
Description
Calculates the number of true positives
Usage
metric_true_positives(..., 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 positives. This metric creates one local variable, true_positives
that is used to keep track of the number of true positives. 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_negatives()