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# frozen_string_literal: true
require 'rumale/base/evaluator'
module Rumale
module EvaluationMeasure
# ExplainedVarianceScore is a class that calculates the explained variance score.
#
# @example
# evaluator = Rumale::EvaluationMeasure::ExplainedVarianceScore.new
# puts evaluator.score(ground_truth, predicted)
class ExplainedVarianceScore
include Base::Evaluator
# Calculate explained variance score.
#
# @param y_true [Numo::DFloat] (shape: [n_samples, n_outputs]) Ground truth target values.
# @param y_pred [Numo::DFloat] (shape: [n_samples, n_outputs]) Estimated target values.
# @return [Float] Explained variance score.
def score(y_true, y_pred)
y_true = check_convert_tvalue_array(y_true)
y_pred = check_convert_tvalue_array(y_pred)
raise ArgumentError, 'Expect to have the same size both y_true and y_pred.' unless y_true.shape == y_pred.shape
diff = y_true - y_pred
numerator = ((diff - diff.mean(0))**2).mean(0)
denominator = ((y_true - y_true.mean(0))**2).mean(0)
n_outputs = y_true.shape[1]
if n_outputs.nil?
denominator.zero? ? 0 : 1.0 - numerator / denominator
else
valids = denominator.ne(0)
(1.0 - numerator[valids] / denominator[valids]).sum / n_outputs
end
end
end
end
end
Version data entries
40 entries across 40 versions & 1 rubygems