XGBoost交叉验证

Question

当我尝试使用代码运行交叉宣传时：

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

我有以下错误：

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:ProgramDataAnaconda35libsite-packagesxgboost-0.40-py3.6.eggxgboost.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:ProgramDataAnaconda35libsite-packagesxgboost-0.40-py3.6.eggxgboost.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:ProgramDataAnaconda35libsite-packagesxgboost-0.40-py3.6.eggxgboost.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

您正在传递参数值n_fold=1这是没有意义的。交叉验证是关于在几个分区中对数据进行分区，并验证将其中一个分区的模型验证。因此1是一个无效的值，请尝试n_fold=3 or higher。那么您的错误应该消失。

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