code: def create_xgboost_classifier(X, y):
      """Create an XGBoost classifier.
  
      :param X: The training data.
      :type X: numpy.ndarray or pandas.DataFrame
      :param y: The training labels.
      :type y: numpy.ndarray or pandas.DataFrame
      :return: An XGBoost classifier.
      :rtype: xgboost.XGBClassifier
      """
      xgb = XGBClassifier(
          learning_rate=0.1,
          max_depth=3,
          n_estimators=100,
          n_jobs=1,
          random_state=777,
      )
      model = xgb.fit(X, y)
      return model
  
label_desc: Use image node_id 1 for calling a global function with example usage: create_xgboost_classifier(X, y) and returns: model