XGBoost: what's wrong with my xgb.cv call syntax?

Question

I'm trying to use xgboost on Python.

Here is my code. xgb.train works but I get on error with xgb.cv although it seems I used it the correct way.

The following works for me:

###### 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)

But if I change the line:

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

to this:

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

I get the following unexpected error:

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

EDIT: following the advice below from @martineau, and trying this

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

yields this error

TypeError Traceback (most recent call last) in () 43 # bst = xgb.train( plst, dtrain, num_round, evallist,early_stopping_rounds=5 ) # early_stopping_rounds=10 # when there is a validation set 44 ---> 45 bst.res=xgb.cv(plst,dtrain,num_round,evallist,nfold = 5,early_stopping_rounds=5) 46 47 bst.save_model('0001.model')

TypeError: cv() got multiple values for keyword argument 'nfold'

Answer 1

You can't use evallist in cv. So you should remove evallist from the arguments of the xgb.cv call. Put another way, you should try:

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

instead of

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

Chris, the python training API slightly changed between the pip version and the current master branch in github. They mainly added the keyword args verbose_eval, callbacks and folds to the cv function. The verbose_eval and callbacks keywords were already there in the pip version for the train function but not for the cv one.