Question

当我尝试使用代码运行交叉价值时：

cv_results = xgb.cv(params=params,dtrain=dmatrix_train, num_boost_round=10, nfold=1)

我收到以下错误：

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

Answer 1

您传递参数值n_fold=1这没有意义。交叉验证是关于在几个分区中对数据进行分区并验证模型中的一个分区。所以1是无效值，请尝试n_fold=3 or higher。然后你的错误应该消失了。

在此处阅读有关交叉验证的更多信息。 http://scikit-learn.org/stable/modules/cross_validation.html

XGBoost交叉验证

1 个答案: