AI Platform Data Labeling Service V1beta1 API - Class Google::Cloud::DataLabeling::V1beta1::PrCurve::ConfidenceMetricsEntry (v0.5.0)

Reference documentation and code samples for the AI Platform Data Labeling Service V1beta1 API class Google::Cloud::DataLabeling::V1beta1::PrCurve::ConfidenceMetricsEntry.

Inherits

  • Object

Extended By

  • Google::Protobuf::MessageExts::ClassMethods

Includes

  • Google::Protobuf::MessageExts

Methods

#confidence_threshold

def confidence_threshold() -> ::Float
Returns
  • (::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.

#confidence_threshold=

def confidence_threshold=(value) -> ::Float
Parameter
  • value (::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.

Returns
  • (::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.

#f1_score

def f1_score() -> ::Float
Returns
  • (::Float) — Harmonic mean of recall and precision.

#f1_score=

def f1_score=(value) -> ::Float
Parameter
  • value (::Float) — Harmonic mean of recall and precision.
Returns
  • (::Float) — Harmonic mean of recall and precision.

#f1_score_at1

def f1_score_at1() -> ::Float
Returns

#f1_score_at1=

def f1_score_at1=(value) -> ::Float
Parameter
Returns

#f1_score_at5

def f1_score_at5() -> ::Float
Returns

#f1_score_at5=

def f1_score_at5=(value) -> ::Float
Parameter
Returns

#precision

def precision() -> ::Float
Returns
  • (::Float) — Precision value.

#precision=

def precision=(value) -> ::Float
Parameter
  • value (::Float) — Precision value.
Returns
  • (::Float) — Precision value.

#precision_at1

def precision_at1() -> ::Float
Returns
  • (::Float) — Precision value for entries with label that has highest score.

#precision_at1=

def precision_at1=(value) -> ::Float
Parameter
  • value (::Float) — Precision value for entries with label that has highest score.
Returns
  • (::Float) — Precision value for entries with label that has highest score.

#precision_at5

def precision_at5() -> ::Float
Returns
  • (::Float) — Precision value for entries with label that has highest 5 scores.

#precision_at5=

def precision_at5=(value) -> ::Float
Parameter
  • value (::Float) — Precision value for entries with label that has highest 5 scores.
Returns
  • (::Float) — Precision value for entries with label that has highest 5 scores.

#recall

def recall() -> ::Float
Returns
  • (::Float) — Recall value.

#recall=

def recall=(value) -> ::Float
Parameter
  • value (::Float) — Recall value.
Returns
  • (::Float) — Recall value.

#recall_at1

def recall_at1() -> ::Float
Returns
  • (::Float) — Recall value for entries with label that has highest score.

#recall_at1=

def recall_at1=(value) -> ::Float
Parameter
  • value (::Float) — Recall value for entries with label that has highest score.
Returns
  • (::Float) — Recall value for entries with label that has highest score.

#recall_at5

def recall_at5() -> ::Float
Returns
  • (::Float) — Recall value for entries with label that has highest 5 scores.

#recall_at5=

def recall_at5=(value) -> ::Float
Parameter
  • value (::Float) — Recall value for entries with label that has highest 5 scores.
Returns
  • (::Float) — Recall value for entries with label that has highest 5 scores.