Class: SVMKit::EvaluationMeasure::Precision

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

Overview

Precision is a class that calculates the preicision of the predicted labels.

Examples:

evaluator = SVMKit::EvaluationMeasure::Precision.new
puts evaluator.score(ground_truth, predicted)

Instance Attribute Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize(average: 'binary') ⇒ Precision

Create a new evaluation measure calculater for precision score.

Parameters:

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

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



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# File 'lib/svmkit/evaluation_measure/precision.rb', line 26

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

Instance Attribute Details

#averageString (readonly)

Return the average type for calculation of precision.

Returns:

  • (String)

    (‘binary’, ‘micro’, ‘macro’)



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# File 'lib/svmkit/evaluation_measure/precision.rb', line 21

def average
  @average
end

Instance Method Details

#score(y_true, y_pred) ⇒ Float

Calculate average precision.

Parameters:

  • y_true (Numo::Int32)

    (shape: [n_samples]) Ground truth labels.

  • y_pred (Numo::Int32)

    (shape: [n_samples]) Predicted labels.

Returns:

  • (Float)

    Average precision



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# File 'lib/svmkit/evaluation_measure/precision.rb', line 36

def score(y_true, y_pred)
  SVMKit::Validation.check_label_array(y_true)
  SVMKit::Validation.check_label_array(y_pred)

  case @average
  when 'binary'
    precision_each_class(y_true, y_pred).last
  when 'micro'
    micro_average_precision(y_true, y_pred)
  when 'macro'
    macro_average_precision(y_true, y_pred)
  end
end