code: def _root_mean_square_error(y, y_pred, w):
      """Calculate the root mean square error."""
      return np.sqrt(np.average(((y_pred - y) ** 2), weights=w))
  
file_path: gplearn/gplearn/fitness.py
imports: import numbers
  import numpy
  from joblib import wrap_non_picklable_objects
  from scipy.stats import rankdata
label_desc: Use image node_id 6 for calling a global function with example usage: _root_mean_square_error(y, y_pred, w) and returns: np