code: def quadratic(x):
      """
      Second order polynomial (quadratic, p = n*(n-1)/2+n+1) regression model.
  
      x --> f(x) = [ 1, { x_i, i = 1,...,n }, { x_i * x_j,  (i,j) = 1,...,n } ].T
                                                            i > j
  
      Parameters
      ----------
      x : array_like
          An array with shape (n_eval, n_features) giving the locations x at
          which the regression model should be evaluated.
  
      Returns
      -------
      f : array_like
          An array with shape (n_eval, p) with the values of the regression
          model.
      """
  
      x = np.asarray(x, dtype=np.float64)
      n_eval, n_features = x.shape
      f = np.hstack([np.ones([n_eval, 1]), x])
      for k in range(n_features):
          f = np.hstack([f, x[:, k, np.newaxis] * x[:, k:]])
  
      return f
  
label_desc: Use image node_id 3 for calling a global function with example usage: quadratic(x) and returns: f