class Google::Apis::BigqueryV2::BinaryConfusionMatrix
Confusion matrix for binary classification models.
Attributes
The fraction of predictions given the correct label. Corresponds to the JSON property `accuracy` @return [Float]
The equally weighted average of recall and precision. Corresponds to the JSON property `f1Score` @return [Float]
Number of false samples predicted as false. Corresponds to the JSON property `falseNegatives` @return [Fixnum]
Number of false samples predicted as true. Corresponds to the JSON property `falsePositives` @return [Fixnum]
Threshold value used when computing each of the following metric. Corresponds to the JSON property `positiveClassThreshold` @return [Float]
The fraction of actual positive predictions that had positive actual labels. Corresponds to the JSON property `precision` @return [Float]
The fraction of actual positive labels that were given a positive prediction. Corresponds to the JSON property `recall` @return [Float]
Number of true samples predicted as false. Corresponds to the JSON property `trueNegatives` @return [Fixnum]
Number of true samples predicted as true. Corresponds to the JSON property `truePositives` @return [Fixnum]
Public Class Methods
# File lib/google/apis/bigquery_v2/classes.rb, line 907 def initialize(**args) update!(**args) end
Public Instance Methods
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