Sha256: 1b8d3b4d482a7467d6bfd506084ec04ac767a9c6ea7c43c2447b9ea1b5c78ad6
Contents?: true
Size: 1.01 KB
Versions: 28
Compression:
Stored size: 1.01 KB
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
# evaluator = Rumale::EvaluationMeasure::MeanSquaredError.new
# puts evaluator.score(ground_truth, predicted)
class MeanSquaredLogError
include 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)
check_tvalue_array(y_true)
check_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
((Numo::NMath.log(y_true + 1) - Numo::NMath.log(y_pred + 1))**2).mean
end
end
end
end
Version data entries
28 entries across 28 versions & 1 rubygems