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Contents
# frozen_string_literal: true
require 'rumale/base/evaluator'
module Rumale
module EvaluationMeasure
# MeanSquaredLogError is a class that calculates the mean squared logarithmic error.
#
# @example
# require 'rumale/evaluation_measure/mean_squared_log_error'
#
# evaluator = Rumale::EvaluationMeasure::MeanSquaredLogError.new
# puts evaluator.score(ground_truth, predicted)
class MeanSquaredLogError
include ::Rumale::Base::Evaluator
# Calculate mean squared logarithmic error.
#
# @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] Mean squared logarithmic error.
def score(y_true, y_pred)
((Numo::NMath.log(y_true + 1) - Numo::NMath.log(y_pred + 1))**2).mean
end
end
end
end
Version data entries
7 entries across 7 versions & 1 rubygems