code: def independentlinear60__gbm():
      """Gradient Boosted Trees"""
      import xgboost
  
      # max_depth and learning_rate were fixed then n_estimators was chosen using a train/test split
      return xgboost.XGBRegressor(
          max_depth=6,
          n_estimators=100,
          learning_rate=0.1,
          n_jobs=8,
          random_state=0,
      )
  
imports: import numpy
  import sklearn
  import sklearn.ensemble
  from sklearn.preprocessing import StandardScaler
label_desc: Use image node_id 11 for calling a global function with example usage: independentlinear60__gbm() and returns: xgboost