GoogleApi.BigQuery.V2.Model.BinaryConfusionMatrix (google_api_big_query v0.88.0)

Confusion matrix for binary classification models.

Attributes

accuracy (type: float(), default: nil) - The fraction of predictions given the correct label.
f1Score (type: float(), default: nil) - The equally weighted average of recall and precision.
falseNegatives (type: String.t, default: nil) - Number of false samples predicted as false.
falsePositives (type: String.t, default: nil) - Number of false samples predicted as true.
positiveClassThreshold (type: float(), default: nil) - Threshold value used when computing each of the following metric.
precision (type: float(), default: nil) - The fraction of actual positive predictions that had positive actual labels.
recall (type: float(), default: nil) - The fraction of actual positive labels that were given a positive prediction.
trueNegatives (type: String.t, default: nil) - Number of true samples predicted as false.
truePositives (type: String.t, default: nil) - Number of true samples predicted as true.

Summary

Types

t()

Functions

decode(value, options)

Unwrap a decoded JSON object into its complex fields.

Types

t()

@type t() :: %GoogleApi.BigQuery.V2.Model.BinaryConfusionMatrix{
  accuracy: float() | nil,
  f1Score: float() | nil,
  falseNegatives: String.t() | nil,
  falsePositives: String.t() | nil,
  positiveClassThreshold: float() | nil,
  precision: float() | nil,
  recall: float() | nil,
  trueNegatives: String.t() | nil,
  truePositives: String.t() | nil
}

Functions

decode(value, options)

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

Unwrap a decoded JSON object into its complex fields.