Class: Google::Apis::BigqueryV2::BinaryConfusionMatrix

Inherits:
Object
  • Object
show all
Includes:
Core::Hashable, Core::JsonObjectSupport
Defined in:
lib/google/apis/bigquery_v2/classes.rb,
lib/google/apis/bigquery_v2/representations.rb,
lib/google/apis/bigquery_v2/representations.rb

Overview

Confusion matrix for binary classification models.

Instance Attribute Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize(**args) ⇒ BinaryConfusionMatrix

Returns a new instance of BinaryConfusionMatrix.



831
832
833
 
# File 'lib/google/apis/bigquery_v2/classes.rb', line 831

def initialize(**args)
   update!(**args)
end

Instance Attribute Details

#accuracy ⇒ Float

The fraction of predictions given the correct label. Corresponds to the JSON property accuracy

Returns:

  • (Float) 


789
790
791
 
# File 'lib/google/apis/bigquery_v2/classes.rb', line 789

def accuracy
  @accuracy
end

#f1_score ⇒ Float

The equally weighted average of recall and precision. Corresponds to the JSON property f1Score

Returns:

  • (Float) 


794
795
796
 
# File 'lib/google/apis/bigquery_v2/classes.rb', line 794

def f1_score
  @f1_score
end

#false_negatives ⇒ Fixnum

Number of false samples predicted as false. Corresponds to the JSON property falseNegatives

Returns:

  • (Fixnum) 


799
800
801
 
# File 'lib/google/apis/bigquery_v2/classes.rb', line 799

def false_negatives
  @false_negatives
end

#false_positives ⇒ Fixnum

Number of false samples predicted as true. Corresponds to the JSON property falsePositives

Returns:

  • (Fixnum) 


804
805
806
 
# File 'lib/google/apis/bigquery_v2/classes.rb', line 804

def false_positives
  @false_positives
end

#positive_class_threshold ⇒ Float

Threshold value used when computing each of the following metric. Corresponds to the JSON property positiveClassThreshold

Returns:

  • (Float) 


809
810
811
 
# File 'lib/google/apis/bigquery_v2/classes.rb', line 809

def positive_class_threshold
  @positive_class_threshold
end

#precision ⇒ Float

The fraction of actual positive predictions that had positive actual labels. Corresponds to the JSON property precision

Returns:

  • (Float) 


814
815
816
 
# File 'lib/google/apis/bigquery_v2/classes.rb', line 814

def precision
  @precision
end

#recall ⇒ Float

The fraction of actual positive labels that were given a positive prediction. Corresponds to the JSON property recall

Returns:

  • (Float) 


819
820
821
 
# File 'lib/google/apis/bigquery_v2/classes.rb', line 819

def recall
  @recall
end

#true_negatives ⇒ Fixnum

Number of true samples predicted as false. Corresponds to the JSON property trueNegatives

Returns:

  • (Fixnum) 


824
825
826
 
# File 'lib/google/apis/bigquery_v2/classes.rb', line 824

def true_negatives
  @true_negatives
end

#true_positives ⇒ Fixnum

Number of true samples predicted as true. Corresponds to the JSON property truePositives

Returns:

  • (Fixnum) 


829
830
831
 
# File 'lib/google/apis/bigquery_v2/classes.rb', line 829

def true_positives
  @true_positives
end

Instance Method Details

#update!(**args) ⇒ Object

Update properties of this object



836
837
838
839
840
841
842
843
844
845
846
 
# File 'lib/google/apis/bigquery_v2/classes.rb', line 836

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