View Source GoogleApi.AIPlatform.V1.Model.GoogleCloudAiplatformV1SchemaModelevaluationMetricsClassificationEvaluationMetricsConfidenceMetrics (google_api_ai_platform v0.24.0)

Attributes

  • confidenceThreshold (type: number(), default: nil) - Metrics are computed with an assumption that the Model never returns predictions with score lower than this value.
  • confusionMatrix (type: GoogleApi.AIPlatform.V1.Model.GoogleCloudAiplatformV1SchemaModelevaluationMetricsConfusionMatrix.t, default: nil) - Confusion matrix of the evaluation for this confidence_threshold.
  • f1Score (type: number(), default: nil) - The harmonic mean of recall and precision. For summary metrics, it computes the micro-averaged F1 score.
  • f1ScoreAt1 (type: number(), default: nil) - The harmonic mean of recallAt1 and precisionAt1.
  • f1ScoreMacro (type: number(), default: nil) - Macro-averaged F1 Score.
  • f1ScoreMicro (type: number(), default: nil) - Micro-averaged F1 Score.
  • falseNegativeCount (type: String.t, default: nil) - The number of ground truth labels that are not matched by a Model created label.
  • falsePositiveCount (type: String.t, default: nil) - The number of Model created labels that do not match a ground truth label.
  • falsePositiveRate (type: number(), default: nil) - False Positive Rate for the given confidence threshold.
  • falsePositiveRateAt1 (type: number(), default: nil) - The False Positive Rate when only considering the label that has the highest prediction score and not below the confidence threshold for each DataItem.
  • maxPredictions (type: integer(), default: nil) - Metrics are computed with an assumption that the Model always returns at most this many predictions (ordered by their score, descendingly), but they all still need to meet the confidenceThreshold.
  • precision (type: number(), default: nil) - Precision for the given confidence threshold.
  • precisionAt1 (type: number(), default: nil) - The precision when only considering the label that has the highest prediction score and not below the confidence threshold for each DataItem.
  • recall (type: number(), default: nil) - Recall (True Positive Rate) for the given confidence threshold.
  • recallAt1 (type: number(), default: nil) - The Recall (True Positive Rate) when only considering the label that has the highest prediction score and not below the confidence threshold for each DataItem.
  • trueNegativeCount (type: String.t, default: nil) - The number of labels that were not created by the Model, but if they would, they would not match a ground truth label.
  • truePositiveCount (type: String.t, default: nil) - The number of Model created labels that match a ground truth label.

Summary

Types

t()

Functions

decode(value, options)

Unwrap a decoded JSON object into its complex fields.

Types

t()

@type t() ::
  %GoogleApi.AIPlatform.V1.Model.GoogleCloudAiplatformV1SchemaModelevaluationMetricsClassificationEvaluationMetricsConfidenceMetrics{
    confidenceThreshold: number() | nil,
    confusionMatrix:
      GoogleApi.AIPlatform.V1.Model.GoogleCloudAiplatformV1SchemaModelevaluationMetricsConfusionMatrix.t()
      | nil,
    f1Score: number() | nil,
    f1ScoreAt1: number() | nil,
    f1ScoreMacro: number() | nil,
    f1ScoreMicro: number() | nil,
    falseNegativeCount: String.t() | nil,
    falsePositiveCount: String.t() | nil,
    falsePositiveRate: number() | nil,
    falsePositiveRateAt1: number() | nil,
    maxPredictions: integer() | nil,
    precision: number() | nil,
    precisionAt1: number() | nil,
    recall: number() | nil,
    recallAt1: number() | nil,
    trueNegativeCount: String.t() | nil,
    truePositiveCount: String.t() | nil
  }

Functions

decode(value, options)

@spec decode(struct(), keyword()) :: struct()

Unwrap a decoded JSON object into its complex fields.