XGBoost：我的xgb.cv调用语法出了什么问题？

Question

我正在尝试在Python上使用xgboost。

这是我的代码。 xgb.train有效，但我遇到了xgb.cv错误尽管似乎我使用了正确的方法。

以下为我工作：

###### XGBOOST ######

import datetime
startTime = datetime.datetime.now()

import xgboost as xgb
data_train   = np.array(traindata.drop('Category',axis=1))
labels_train = np.array(traindata['Category'].cat.codes)

data_valid   = np.array(validdata.drop('Category',axis=1))
labels_valid = np.array(validdata['Category'].astype('category').cat.codes)

weights_train = np.ones(len(labels_train))
weights_valid  = np.ones(len(labels_valid ))

dtrain = xgb.DMatrix( data_train, label=labels_train,weight = weights_train)
dvalid  = xgb.DMatrix( data_valid , label=labels_valid ,weight = weights_valid )

param = {'bst:max_depth':5, 'bst:eta':0.05, # eta [default=0.3]
         #'min_child_weight':1,'gamma':0,'subsample':1,'colsample_bytree':1,'scale_pos_weight':0, # default
         # max_delta_step:0 # default
         'min_child_weight':5,'scale_pos_weight':0, 'max_delta_step':2,
         'subsample':0.8,'colsample_bytree':0.8,
         'silent':1, 'objective':'multi:softprob' }

param['nthread'] = 4
param['eval_metric'] = 'mlogloss'
param['lambda'] = 2
param['num_class']=39

evallist  = [(dtrain,'train'),(dvalid,'eval')] # if there is a validation set
# evallist  = [(dtrain,'train')]                   # if there is no validation set

plst = param.items()
plst += [('ams@0','eval_metric')]

num_round = 100

bst = xgb.train( plst, dtrain, num_round, evallist,early_stopping_rounds=5 ) # early_stopping_rounds=10 # when there is a validation set

# bst.res=xgb.cv(plst,dtrain,num_round,nfold = 5,evallist,early_stopping_rounds=5)

bst.save_model('0001.model')

# dump model
bst.dump_model('dump.raw.txt')
# dump model with feature map
# bst.dump_model('dump.raw.txt','featmap.txt')

x = datetime.datetime.now() - startTime
print(x)

但是如果我换行：

bst = xgb.train( plst, dtrain, num_round, evallist,early_stopping_rounds=5 )

对此：

bst.res=xgb.cv(plst,dtrain,num_round,nfold = 5,evallist,early_stopping_rounds=5)

我收到以下意外错误：

File "<ipython-input-46-ebdf0546f464>", line 45
    bst.res=xgb.cv(plst,dtrain,num_round,nfold = 5,evallist,early_stopping_rounds=5) SyntaxError: non-keyword arg after
keyword arg

编辑：遵循@martineau的以下建议，然后尝试此操作

bst.res=xgb.cv(plst,dtrain,num_round,evallist,nfold = 5,early_stopping_rounds=5)

产生此错误

TypeError Traceback（最近的呼叫最后）在（）43＃bst = xgb.train（plst，dtrain，num_round，evallist，early_stopping_rounds = 5）＃early_stopping_rounds = 10＃何时有一个验证集44---> 45 bst.res = xgb.cv（plst，dtrain，num_round，evallist，nfold = 5，early_stopping_rounds = 5）4647 bst.save_model（'0001.model'）

TypeError：cv（）为关键字参数'nfold'获得了多个值

Answer 1

您不能在evallist中使用cv。因此，您应该从evallist调用的参数中删除xgb.cv。换句话说，您应该尝试：

bst.res = xgb.cv(plst, dtrain, num_round, nfold=5, early_stopping_rounds=5)

代替

bst.res=xgb.cv(plst,dtrain,num_round,nfold = 5,evallist,early_stopping_rounds=5)

克里斯，python培训API在pip版本和github中的当前master分支之间略有变化。他们主要在verbose_eval函数中添加了关键字args callbacks，folds和cv。 pip版本中已经存在verbose_eval和callbacks关键字用于train功能，但没有用于cv功能。

Answer 2

我的理解是，此错误是由于通过pip安装xgboost而导致的，而现在已过时。 XGBoost应该改为如下安装：

git clone --recursive https://github.com/dmlc/xgboost
cd xgboost; make -j4 
cd python-package; sudo python setup.py install