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Contents
# frozen_string_literal: true
require 'numo/narray'
module Rumale
module Base
# Module for all regressors in Rumale.
module Regressor
# An abstract method for fitting a model.
def fit
raise NotImplementedError, "#{__method__} has to be implemented in #{self.class}."
end
# An abstract method for predicting labels.
def predict
raise NotImplementedError, "#{__method__} has to be implemented in #{self.class}."
end
# Calculate the coefficient of determination for the given testing data.
#
# @param x [Numo::DFloat] (shape: [n_samples, n_features]) Testing data.
# @param y [Numo::DFloat] (shape: [n_samples, n_outputs]) Target values for testing data.
# @return [Float] Coefficient of determination
def score(x, y)
x = ::Rumale::Validation.check_convert_sample_array(x)
y = ::Rumale::Validation.check_convert_target_value_array(y)
::Rumale::Validation.check_sample_size(x, y)
predicted = predict(x)
n_samples, n_outputs = y.shape
numerator = ((y - predicted)**2).sum(axis: 0)
yt_mean = y.sum(axis: 0) / n_samples
denominator = ((y - yt_mean)**2).sum(axis: 0)
if n_outputs.nil?
denominator.zero? ? 0.0 : 1.0 - numerator.fdiv(denominator)
else
scores = 1.0 - numerator / denominator
scores[denominator.eq(0)] = 0.0
scores.sum.fdiv(scores.size)
end
end
end
end
end
Version data entries
7 entries across 7 versions & 1 rubygems