Class: DbClustering::DistanceMetrics::PearsonCorrelation

Inherits:
Object
  • Object
show all
Includes:
Math
Defined in:
lib/distance_metrics/pearson_correlation.rb

Instance Method Summary collapse

Constructor Details

#initialize(min_dimensions: 1) ⇒ PearsonCorrelation

Returns a new instance of PearsonCorrelation.



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# File 'lib/distance_metrics/pearson_correlation.rb', line 6

def initialize(min_dimensions: 1)
  @min_dimensions = min_dimensions
end

Instance Method Details

#correlation(vector1, vector2) ⇒ Object 



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# File 'lib/distance_metrics/pearson_correlation.rb', line 14

def correlation(vector1, vector2)
  vector1_array = vector1.array_for_comparison(vector2)
  vector2_array = vector2.array_for_comparison(vector1)

  if vector1_array.count != vector2_array.count
    raise "Vectors with different sizes cannot be compared"
  end

  if vector1_array.count < @min_dimensions
    return Float::INFINITY
  end

  # see here for calculation formula: http://en.wikipedia.org/wiki/Pearson_product-moment_correlation_coefficient
  v1_mean = vector1_array.reduce(:+) / vector1_array.count.to_f
  v2_mean = vector2_array.reduce(:+) / vector2_array.count.to_f

  numerator = 0
  vector1_array.count.times do |i|
    numerator += (vector1_array[i] - v1_mean) * (vector2_array[i] - v2_mean)
  end

  left_sqrt = sqrt(vector1_array.reduce(0) { |sum, v1i| sum + (v1i - v1_mean) ** 2 })
  right_sqrt = sqrt(vector2_array.reduce(0) { |sum, v2i| sum + (v2i - v2_mean) ** 2 })
  denominator = left_sqrt * right_sqrt

  numerator.to_f / denominator
end

#distance(vector1, vector2) ⇒ Object 



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# File 'lib/distance_metrics/pearson_correlation.rb', line 10

def distance(vector1, vector2)
  1.0 - correlation(vector1, vector2)
end