code: def mse(targets, predictions):
      return np.mean((np.array(targets) - np.array(predictions)) ** 2)
  
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 4 for calling a global function with example usage: mse(targets, predictions) and returns: np