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我正在努力研究如何在 sklearn 中实现 TimeSeriesSplit。

下面链接中的建议答案产生了相同的 ValueError。

sklearn TimeSeriesSplit cross_val_predict 仅适用于分区

这里是我的代码中的相关位：

from sklearn.model_selection import cross_val_predict
from sklearn import svm

features = df[df.columns[0:6]]
target = df['target']

clf = svm.SVC(random_state=0)

pred = cross_val_predict(clf, features, target, cv=TimeSeriesSplit(n_splits=5).split(features))

ValueError                                Traceback (most recent call last)
<ipython-input-57-d1393cd05640> in <module>()
----> 1 pred = cross_val_predict(clf, features, target, cv=TimeSeriesSplit(n_splits=5).split(features))

/home/jedwards/anaconda3/envs/py36/lib/python3.6/site-packages/sklearn/model_selection/_validation.py in cross_val_predict(estimator, X, y, groups, cv, n_jobs, verbose, fit_params, pre_dispatch, method)
    407 
    408     if not _check_is_permutation(test_indices, _num_samples(X)):
--> 409         raise ValueError('cross_val_predict only works for partitions')
    410 
    411     inv_test_indices …