Class: Rumale::EvaluationMeasure::FScore

Inherits:
Object
  • Object
show all
Includes:
Base::Evaluator
Defined in:
lib/rumale/evaluation_measure/f_score.rb

Overview

FScore is a class that calculates the F1-score of the predicted labels.

Examples:

evaluator = Rumale::EvaluationMeasure::FScore.new
puts evaluator.score(ground_truth, predicted)

Instance Attribute Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize(average: 'binary') ⇒ FScore

Create a new evaluation measure calculater for F1-score.

Parameters:

  • average (String) (defaults to: 'binary') —

    The average type (‘binary’, ‘micro’, ‘macro’)



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# File 'lib/rumale/evaluation_measure/f_score.rb', line 25

def initialize(average: 'binary')
  check_params_string(average: average)
  @average = average
end

Instance Attribute Details

#average ⇒ String (readonly)

Return the average type for calculation of F1-score.

Returns:

  • (String) —

    (‘binary’, ‘micro’, ‘macro’)



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# File 'lib/rumale/evaluation_measure/f_score.rb', line 20

def average
  @average
end

Instance Method Details

#score(y_true, y_pred) ⇒ Float

Calculate average F1-score

Parameters:

  • y_true (Numo::Int32) —

    (shape: [n_samples]) Ground truth labels.

  • y_pred (Numo::Int32) —

    (shape: [n_samples]) Predicted labels.

Returns:

  • (Float) —

    Average F1-score



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# File 'lib/rumale/evaluation_measure/f_score.rb', line 35

def score(y_true, y_pred)
  check_label_array(y_true)
  check_label_array(y_pred)

  case @average
  when 'binary'
    f_score_each_class(y_true, y_pred).last
  when 'micro'
    micro_average_f_score(y_true, y_pred)
  when 'macro'
    macro_average_f_score(y_true, y_pred)
  end
end