google_api_big_query v0.13.0 GoogleApi.BigQuery.V2.Model.BinaryConfusionMatrix View Source

Confusion matrix for binary classification models.

Attributes

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

Link to this section Summary

Functions

Unwrap a decoded JSON object into its complex fields.

Link to this section Types

Link to this type

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

Link to this section Functions

Link to this function

decode(value, options) View Source
decode(struct(), keyword()) :: struct()

Unwrap a decoded JSON object into its complex fields.