Class: Google::Cloud::DataLabeling::V1beta1::PrCurve

Inherits:
Object
  • Object
show all
Extended by:
Protobuf::MessageExts::ClassMethods
Includes:
Protobuf::MessageExts
Defined in:
proto_docs/google/cloud/datalabeling/v1beta1/evaluation.rb

Defined Under Namespace

Classes: ConfidenceMetricsEntry

Instance Attribute Summary collapse

Instance Attribute Details

#annotation_spec ⇒ ::Google::Cloud::DataLabeling::V1beta1::AnnotationSpec

Returns 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:



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# File 'proto_docs/google/cloud/datalabeling/v1beta1/evaluation.rb', line 136

class PrCurve
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  # @!attribute [rw] confidence_threshold
  #   @return [::Float]
  #     Threshold used for this entry.
  #
  #     For classification tasks, this is a classification threshold: a
  #     predicted label is categorized as positive or negative (in the context of
  #     this point on the PR curve) based on whether the label's score meets this
  #     threshold.
  #
  #     For image object detection (bounding box) tasks, this is the
  #     [intersection-over-union
  #
  #     (IOU)](/vision/automl/object-detection/docs/evaluate#intersection-over-union)
  #     threshold for the context of this point on the PR curve.
  # @!attribute [rw] recall
  #   @return [::Float]
  #     Recall value.
  # @!attribute [rw] precision
  #   @return [::Float]
  #     Precision value.
  # @!attribute [rw] f1_score
  #   @return [::Float]
  #     Harmonic mean of recall and precision.
  # @!attribute [rw] recall_at1
  #   @return [::Float]
  #     Recall value for entries with label that has highest score.
  # @!attribute [rw] precision_at1
  #   @return [::Float]
  #     Precision value for entries with label that has highest score.
  # @!attribute [rw] f1_score_at1
  #   @return [::Float]
  #     The harmonic mean of {::Google::Cloud::DataLabeling::V1beta1::PrCurve::ConfidenceMetricsEntry#recall_at1 recall_at1} and {::Google::Cloud::DataLabeling::V1beta1::PrCurve::ConfidenceMetricsEntry#precision_at1 precision_at1}.
  # @!attribute [rw] recall_at5
  #   @return [::Float]
  #     Recall value for entries with label that has highest 5 scores.
  # @!attribute [rw] precision_at5
  #   @return [::Float]
  #     Precision value for entries with label that has highest 5 scores.
  # @!attribute [rw] f1_score_at5
  #   @return [::Float]
  #     The harmonic mean of {::Google::Cloud::DataLabeling::V1beta1::PrCurve::ConfidenceMetricsEntry#recall_at5 recall_at5} and {::Google::Cloud::DataLabeling::V1beta1::PrCurve::ConfidenceMetricsEntry#precision_at5 precision_at5}.
  class ConfidenceMetricsEntry
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end
end

#area_under_curve ⇒ ::Float

Returns 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.



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# File 'proto_docs/google/cloud/datalabeling/v1beta1/evaluation.rb', line 136

class PrCurve
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  # @!attribute [rw] confidence_threshold
  #   @return [::Float]
  #     Threshold used for this entry.
  #
  #     For classification tasks, this is a classification threshold: a
  #     predicted label is categorized as positive or negative (in the context of
  #     this point on the PR curve) based on whether the label's score meets this
  #     threshold.
  #
  #     For image object detection (bounding box) tasks, this is the
  #     [intersection-over-union
  #
  #     (IOU)](/vision/automl/object-detection/docs/evaluate#intersection-over-union)
  #     threshold for the context of this point on the PR curve.
  # @!attribute [rw] recall
  #   @return [::Float]
  #     Recall value.
  # @!attribute [rw] precision
  #   @return [::Float]
  #     Precision value.
  # @!attribute [rw] f1_score
  #   @return [::Float]
  #     Harmonic mean of recall and precision.
  # @!attribute [rw] recall_at1
  #   @return [::Float]
  #     Recall value for entries with label that has highest score.
  # @!attribute [rw] precision_at1
  #   @return [::Float]
  #     Precision value for entries with label that has highest score.
  # @!attribute [rw] f1_score_at1
  #   @return [::Float]
  #     The harmonic mean of {::Google::Cloud::DataLabeling::V1beta1::PrCurve::ConfidenceMetricsEntry#recall_at1 recall_at1} and {::Google::Cloud::DataLabeling::V1beta1::PrCurve::ConfidenceMetricsEntry#precision_at1 precision_at1}.
  # @!attribute [rw] recall_at5
  #   @return [::Float]
  #     Recall value for entries with label that has highest 5 scores.
  # @!attribute [rw] precision_at5
  #   @return [::Float]
  #     Precision value for entries with label that has highest 5 scores.
  # @!attribute [rw] f1_score_at5
  #   @return [::Float]
  #     The harmonic mean of {::Google::Cloud::DataLabeling::V1beta1::PrCurve::ConfidenceMetricsEntry#recall_at5 recall_at5} and {::Google::Cloud::DataLabeling::V1beta1::PrCurve::ConfidenceMetricsEntry#precision_at5 precision_at5}.
  class ConfidenceMetricsEntry
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end
end

#confidence_metrics_entries ⇒ ::Array<::Google::Cloud::DataLabeling::V1beta1::PrCurve::ConfidenceMetricsEntry>

Returns Entries that make up the precision-recall graph. Each entry is a "point" on the graph drawn for a different confidence_threshold.

Returns:



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# File 'proto_docs/google/cloud/datalabeling/v1beta1/evaluation.rb', line 136

class PrCurve
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  # @!attribute [rw] confidence_threshold
  #   @return [::Float]
  #     Threshold used for this entry.
  #
  #     For classification tasks, this is a classification threshold: a
  #     predicted label is categorized as positive or negative (in the context of
  #     this point on the PR curve) based on whether the label's score meets this
  #     threshold.
  #
  #     For image object detection (bounding box) tasks, this is the
  #     [intersection-over-union
  #
  #     (IOU)](/vision/automl/object-detection/docs/evaluate#intersection-over-union)
  #     threshold for the context of this point on the PR curve.
  # @!attribute [rw] recall
  #   @return [::Float]
  #     Recall value.
  # @!attribute [rw] precision
  #   @return [::Float]
  #     Precision value.
  # @!attribute [rw] f1_score
  #   @return [::Float]
  #     Harmonic mean of recall and precision.
  # @!attribute [rw] recall_at1
  #   @return [::Float]
  #     Recall value for entries with label that has highest score.
  # @!attribute [rw] precision_at1
  #   @return [::Float]
  #     Precision value for entries with label that has highest score.
  # @!attribute [rw] f1_score_at1
  #   @return [::Float]
  #     The harmonic mean of {::Google::Cloud::DataLabeling::V1beta1::PrCurve::ConfidenceMetricsEntry#recall_at1 recall_at1} and {::Google::Cloud::DataLabeling::V1beta1::PrCurve::ConfidenceMetricsEntry#precision_at1 precision_at1}.
  # @!attribute [rw] recall_at5
  #   @return [::Float]
  #     Recall value for entries with label that has highest 5 scores.
  # @!attribute [rw] precision_at5
  #   @return [::Float]
  #     Precision value for entries with label that has highest 5 scores.
  # @!attribute [rw] f1_score_at5
  #   @return [::Float]
  #     The harmonic mean of {::Google::Cloud::DataLabeling::V1beta1::PrCurve::ConfidenceMetricsEntry#recall_at5 recall_at5} and {::Google::Cloud::DataLabeling::V1beta1::PrCurve::ConfidenceMetricsEntry#precision_at5 precision_at5}.
  class ConfidenceMetricsEntry
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end
end

#mean_average_precision ⇒ ::Float

Returns Mean average prcision of this curve.

Returns:

  • (::Float) —

    Mean average prcision of this curve.



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# File 'proto_docs/google/cloud/datalabeling/v1beta1/evaluation.rb', line 136

class PrCurve
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  # @!attribute [rw] confidence_threshold
  #   @return [::Float]
  #     Threshold used for this entry.
  #
  #     For classification tasks, this is a classification threshold: a
  #     predicted label is categorized as positive or negative (in the context of
  #     this point on the PR curve) based on whether the label's score meets this
  #     threshold.
  #
  #     For image object detection (bounding box) tasks, this is the
  #     [intersection-over-union
  #
  #     (IOU)](/vision/automl/object-detection/docs/evaluate#intersection-over-union)
  #     threshold for the context of this point on the PR curve.
  # @!attribute [rw] recall
  #   @return [::Float]
  #     Recall value.
  # @!attribute [rw] precision
  #   @return [::Float]
  #     Precision value.
  # @!attribute [rw] f1_score
  #   @return [::Float]
  #     Harmonic mean of recall and precision.
  # @!attribute [rw] recall_at1
  #   @return [::Float]
  #     Recall value for entries with label that has highest score.
  # @!attribute [rw] precision_at1
  #   @return [::Float]
  #     Precision value for entries with label that has highest score.
  # @!attribute [rw] f1_score_at1
  #   @return [::Float]
  #     The harmonic mean of {::Google::Cloud::DataLabeling::V1beta1::PrCurve::ConfidenceMetricsEntry#recall_at1 recall_at1} and {::Google::Cloud::DataLabeling::V1beta1::PrCurve::ConfidenceMetricsEntry#precision_at1 precision_at1}.
  # @!attribute [rw] recall_at5
  #   @return [::Float]
  #     Recall value for entries with label that has highest 5 scores.
  # @!attribute [rw] precision_at5
  #   @return [::Float]
  #     Precision value for entries with label that has highest 5 scores.
  # @!attribute [rw] f1_score_at5
  #   @return [::Float]
  #     The harmonic mean of {::Google::Cloud::DataLabeling::V1beta1::PrCurve::ConfidenceMetricsEntry#recall_at5 recall_at5} and {::Google::Cloud::DataLabeling::V1beta1::PrCurve::ConfidenceMetricsEntry#precision_at5 precision_at5}.
  class ConfidenceMetricsEntry
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods
  end
end