script_xg.py 文件源码

def runXGB(train_X, train_y, seed_val=123):
  param = {}
  param['objective'] = 'multi:softprob'
  param['eta'] = 0.05
  param['max_depth'] = 6
  param['silent'] = 1
  param['num_class'] = 22
  param['eval_metric'] = "mlogloss"
  param['min_child_weight'] = 2
  param['subsample'] = 0.9
  param['colsample_bytree'] = 0.9
  param['seed'] = seed_val
  num_rounds = 115

  plst = list(param.items())
  xgtrain = xgb.DMatrix(train_X, label=train_y)
  model = xgb.train(plst, xgtrain, num_rounds)  
  return model