Class: Google::Cloud::AutoML::V1beta1::BoundingBoxMetricsEntry
- Inherits:
-
Object
- Object
- Google::Cloud::AutoML::V1beta1::BoundingBoxMetricsEntry
- Defined in:
- lib/google/cloud/automl/v1beta1/doc/google/cloud/automl/v1beta1/detection.rb
Overview
Bounding box matching model metrics for a single intersection-over-union threshold and multiple label match confidence thresholds.
Defined Under Namespace
Classes: ConfidenceMetricsEntry
Instance Attribute Summary collapse
-
#confidence_metrics_entries ⇒ Array<Google::Cloud::AutoML::V1beta1::BoundingBoxMetricsEntry::ConfidenceMetricsEntry>
Output only.
-
#iou_threshold ⇒ Float
Output only.
-
#mean_average_precision ⇒ Float
Output only.
Instance Attribute Details
#confidence_metrics_entries ⇒ Array<Google::Cloud::AutoML::V1beta1::BoundingBoxMetricsEntry::ConfidenceMetricsEntry>
Returns Output only. Metrics for each label-match confidence_threshold from 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99. Precision-recall curve is derived from them.
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# File 'lib/google/cloud/automl/v1beta1/doc/google/cloud/automl/v1beta1/detection.rb', line 71 class BoundingBoxMetricsEntry # Metrics for a single confidence threshold. # @!attribute [rw] confidence_threshold # @return [Float] # Output only. The confidence threshold value used to compute the metrics. # @!attribute [rw] recall # @return [Float] # Output only. Recall under the given confidence threshold. # @!attribute [rw] precision # @return [Float] # Output only. Precision under the given confidence threshold. # @!attribute [rw] f1_score # @return [Float] # Output only. The harmonic mean of recall and precision. class ConfidenceMetricsEntry; end end |
#iou_threshold ⇒ Float
Returns Output only. The intersection-over-union threshold value used to compute this metrics entry.
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# File 'lib/google/cloud/automl/v1beta1/doc/google/cloud/automl/v1beta1/detection.rb', line 71 class BoundingBoxMetricsEntry # Metrics for a single confidence threshold. # @!attribute [rw] confidence_threshold # @return [Float] # Output only. The confidence threshold value used to compute the metrics. # @!attribute [rw] recall # @return [Float] # Output only. Recall under the given confidence threshold. # @!attribute [rw] precision # @return [Float] # Output only. Precision under the given confidence threshold. # @!attribute [rw] f1_score # @return [Float] # Output only. The harmonic mean of recall and precision. class ConfidenceMetricsEntry; end end |
#mean_average_precision ⇒ Float
Returns Output only. The mean average precision, most often close to au_prc.
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# File 'lib/google/cloud/automl/v1beta1/doc/google/cloud/automl/v1beta1/detection.rb', line 71 class BoundingBoxMetricsEntry # Metrics for a single confidence threshold. # @!attribute [rw] confidence_threshold # @return [Float] # Output only. The confidence threshold value used to compute the metrics. # @!attribute [rw] recall # @return [Float] # Output only. Recall under the given confidence threshold. # @!attribute [rw] precision # @return [Float] # Output only. Precision under the given confidence threshold. # @!attribute [rw] f1_score # @return [Float] # Output only. The harmonic mean of recall and precision. class ConfidenceMetricsEntry; end end |