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Contents
# frozen_string_literal: true
require 'svmkit/validation'
require 'svmkit/base/evaluator'
module SVMKit
module EvaluationMeasure
# Purity is a class that calculates the purity of cluatering results.
#
# @example
# evaluator = SVMKit::EvaluationMeasure::Purity.new
# puts evaluator.score(ground_truth, predicted)
#
# *Reference*
# - C D. Manning, P. Raghavan, and H. Schutze, "Introduction to Information Retrieval," Cambridge University Press., 2008.
class Purity
include Base::Evaluator
# Calculate purity
#
# @param y_true [Numo::Int32] (shape: [n_samples]) Ground truth labels.
# @param y_pred [Numo::Int32] (shape: [n_samples]) Predicted cluster labels.
# @return [Float] Purity
def score(y_true, y_pred)
SVMKit::Validation.check_label_array(y_true)
SVMKit::Validation.check_label_array(y_pred)
# initiazlie some variables.
purity = 0
n_samples = y_pred.size
class_ids = y_true.to_a.uniq
cluster_ids = y_pred.to_a.uniq
# calculate purity.
cluster_ids.each do |k|
pr_sample_ids = y_pred.eq(k).where.to_a
purity += class_ids.map { |j| (pr_sample_ids & y_true.eq(j).where.to_a).size }.max
end
purity.fdiv(n_samples)
end
end
end
end
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11 entries across 11 versions & 1 rubygems