当我尝试使用以下代码运行交叉验证时:
cv_results = xgb.cv(params=params,dtrain=dmatrix_train, num_boost_round=10, nfold=1)我得到以下错误:
TypeError Traceback (most recent call last)
<ipython-input-101-65647e385c18> in <module>()
----> 1 cv_results = xgb.cv(params=params,dtrain=dmatrix_train, num_boost_round=10, nfold=1)
Can anyone point to me what I am doing wrong?
C:\ProgramData\Anaconda35\lib\site-packages\xgboost-0.40-py3.6.egg\xgboost.py in cv(params, dtrain, num_boost_round, nfold, metrics, obj, feval, fpreproc, show_stdv, seed)
798 """
799 results = []
--> 800 cvfolds = mknfold(dtrain, nfold, params, seed, metrics, fpreproc)
801 for i in range(num_boost_round):
802 for f in cvfolds:
C:\ProgramData\Anaconda35\lib\site-packages\xgboost-0.40-py3.6.egg\xgboost.py in mknfold(dall, nfold, param, seed, evals, fpreproc)
722 randidx = np.random.permutation(dall.num_row())
723 kstep = len(randidx) / nfold
--> 724 idset = [randidx[(i * kstep): min(len(randidx), (i + 1) * kstep)] for i in range(nfold)]
725 ret = []
726 for k in range(nfold):
C:\ProgramData\Anaconda35\lib\site-packages\xgboost-0.40-py3.6.egg\xgboost.py in <listcomp>(.0)
722 randidx = np.random.permutation(dall.num_row())
723 kstep = len(randidx) / nfold
--> 724 idset = [randidx[(i * kstep): min(len(randidx), (i + 1) * kstep)] for i in range(nfold)]
725 ret = []
726 for k in range(nfold):
TypeError: slice indices must be integers or None or have an __index__ method发布于 2018-02-23 14:26:56
您正在传递参数值n_fold=1,这没有任何意义。交叉验证就是将数据划分到几个分区中,并验证其中一个分区的模型。因此%1是无效值,请尝试使用n_fold=3 or higher。那么你的错误就应该消失了。
在这里阅读更多关于交叉验证的内容。http://scikit-learn.org/stable/modules/cross_validation.html
https://stackoverflow.com/questions/48938828
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