Reference documentation and code samples for the AI Platform Data Labeling Service V1beta1 API class Google::Cloud::DataLabeling::V1beta1::PrCurve.
Inherits
- Object
Extended By
- Google::Protobuf::MessageExts::ClassMethods
Includes
- Google::Protobuf::MessageExts
Methods
#annotation_spec
def annotation_spec() -> ::Google::Cloud::DataLabeling::V1beta1::AnnotationSpec
Returns
- (::Google::Cloud::DataLabeling::V1beta1::AnnotationSpec) — The annotation spec of the label for which the precision-recall curve calculated. If this field is empty, that means the precision-recall curve is an aggregate curve for all labels.
#annotation_spec=
def annotation_spec=(value) -> ::Google::Cloud::DataLabeling::V1beta1::AnnotationSpec
Parameter
- value (::Google::Cloud::DataLabeling::V1beta1::AnnotationSpec) — The annotation spec of the label for which the precision-recall curve calculated. If this field is empty, that means the precision-recall curve is an aggregate curve for all labels.
Returns
- (::Google::Cloud::DataLabeling::V1beta1::AnnotationSpec) — The annotation spec of the label for which the precision-recall curve calculated. If this field is empty, that means the precision-recall curve is an aggregate curve for all labels.
#area_under_curve
def area_under_curve() -> ::Float
Returns
- (::Float) — Area under the precision-recall curve. Not to be confused with area under a receiver operating characteristic (ROC) curve.
#area_under_curve=
def area_under_curve=(value) -> ::Float
Parameter
- value (::Float) — Area under the precision-recall curve. Not to be confused with area under a receiver operating characteristic (ROC) curve.
Returns
- (::Float) — Area under the precision-recall curve. Not to be confused with area under a receiver operating characteristic (ROC) curve.
#confidence_metrics_entries
def confidence_metrics_entries() -> ::Array<::Google::Cloud::DataLabeling::V1beta1::PrCurve::ConfidenceMetricsEntry>
Returns
-
(::Array<::Google::Cloud::DataLabeling::V1beta1::PrCurve::ConfidenceMetricsEntry>) — Entries that make up the precision-recall graph. Each entry is a "point" on
the graph drawn for a different
confidence_threshold.
#confidence_metrics_entries=
def confidence_metrics_entries=(value) -> ::Array<::Google::Cloud::DataLabeling::V1beta1::PrCurve::ConfidenceMetricsEntry>
Parameter
-
value (::Array<::Google::Cloud::DataLabeling::V1beta1::PrCurve::ConfidenceMetricsEntry>) — Entries that make up the precision-recall graph. Each entry is a "point" on
the graph drawn for a different
confidence_threshold.
Returns
-
(::Array<::Google::Cloud::DataLabeling::V1beta1::PrCurve::ConfidenceMetricsEntry>) — Entries that make up the precision-recall graph. Each entry is a "point" on
the graph drawn for a different
confidence_threshold.
#mean_average_precision
def mean_average_precision() -> ::Float
Returns
- (::Float) — Mean average prcision of this curve.
#mean_average_precision=
def mean_average_precision=(value) -> ::Float
Parameter
- value (::Float) — Mean average prcision of this curve.
Returns
- (::Float) — Mean average prcision of this curve.