cost function for linear regression

cost_function.rb

# features is a Matrix, labels and theta are Vectors
def cost_function(features, labels, theta)
  m = features.row_count
  predictions = predict(features, theta)
  squared_errors = (predictions - labels).map { |error| error**2 }
  (1.0 / (2.0 * m)) * squared_errors.reduce { |a, b| a + b }
end