class Google::Apis::BigqueryV2::BinaryConfusionMatrix

Confusion matrix for binary classification models.

Attributes

accuracy[RW]

The fraction of predictions given the correct label. Corresponds to the JSON property `accuracy` @return [Float]

f1_score[RW]

The equally weighted average of recall and precision. Corresponds to the JSON property `f1Score` @return [Float]

false_negatives[RW]

Number of false samples predicted as false. Corresponds to the JSON property `falseNegatives` @return [Fixnum]

false_positives[RW]

Number of false samples predicted as true. Corresponds to the JSON property `falsePositives` @return [Fixnum]

positive_class_threshold[RW]

Threshold value used when computing each of the following metric. Corresponds to the JSON property `positiveClassThreshold` @return [Float]

precision[RW]

The fraction of actual positive predictions that had positive actual labels. Corresponds to the JSON property `precision` @return [Float]

recall[RW]

The fraction of actual positive labels that were given a positive prediction. Corresponds to the JSON property `recall` @return [Float]

true_negatives[RW]

Number of true samples predicted as false. Corresponds to the JSON property `trueNegatives` @return [Fixnum]

true_positives[RW]

Number of true samples predicted as true. Corresponds to the JSON property `truePositives` @return [Fixnum]

Public Class Methods

new(**args) click to toggle source
# File lib/google/apis/bigquery_v2/classes.rb, line 907
def initialize(**args)
   update!(**args)
end

Public Instance Methods

update!(**args) click to toggle source

Update properties of this object

# File lib/google/apis/bigquery_v2/classes.rb, line 912
def update!(**args)
  @accuracy = args[:accuracy] if args.key?(:accuracy)
  @f1_score = args[:f1_score] if args.key?(:f1_score)
  @false_negatives = args[:false_negatives] if args.key?(:false_negatives)
  @false_positives = args[:false_positives] if args.key?(:false_positives)
  @positive_class_threshold = args[:positive_class_threshold] if args.key?(:positive_class_threshold)
  @precision = args[:precision] if args.key?(:precision)
  @recall = args[:recall] if args.key?(:recall)
  @true_negatives = args[:true_negatives] if args.key?(:true_negatives)
  @true_positives = args[:true_positives] if args.key?(:true_positives)
end