Calculates the number of false positives
metric_false_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
false positives. This metric creates one local variable, accumulator
that is used to keep track of the number of false 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_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(),
metric_true_positives()