code: def no_information_rate(targets, predictions, loss_fn):
      combinations = np.array(list(product(targets, predictions)))
      return loss_fn(combinations[:, 0], combinations[:, 1])
  
file_path: mlxtend/mlxtend/evaluate/bootstrap_point632.py
imports: from itertools import product
  import numpy
  from sklearn.base import clone
  from .bootstrap_outofbag import BootstrapOutOfBag
label_desc: Use image node_id 2 for calling a global function with example usage: no_information_rate(targets, predictions, loss_fn) and returns: loss_fn