docs: def _compute_std_dev(self, X):
          """Computes the standard deviation of a Gaussian Distribution with mean vector X[i]"""
  
          self._sigma = []
          if X.shape[0] <= 1:
              self._sigma = [0.0]
          else:
              for x_mean in range(X.shape[0]):
                  std_dev = np.sqrt(sum([np.linalg.norm(x - x_mean) ** 2 for x in X]) / float(X.shape[0]-1))
                  self._sigma.append(std_dev)
  
          return self._sigma