code: def _random_transformation(fs, x):
      """
      Transform and standardize a vector by a function randomly chosen from
      the function collection.
  
      Parameters
      ----------
      fs : list
          A collection of functions (splines) for transformation.
      x : list
          Feature values to be transformed.
      """
      fi = np.random.choice(range(len(fs)), 1)
      y = fs[fi[0]](x)
      y = _standardize(y)
      return y
  
imports: import random
  import numpy
  import pandas
  from sklearn.datasets import make_classification
  from scipy.optimize import fsolve
  from scipy.special import expit
  from scipy.special import logit
label_desc: Use image node_id 10 for calling a global function with example usage: _random_transformation(fs, x) and returns: y