Calculates the number of true positives
metric_true_positives(..., thresholds = NULL, name = NULL, dtype = NULL)
A (subclassed) Metric
instance that can be passed directly to
compile(metrics = )
, or used as a standalone object. See ?Metric
for
example usage.
Passed on to the underlying metric. Used for forwards and backwards compatibility.
(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.
(Optional) string name of the metric instance.
(Optional) data type of the metric result.
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.
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()