python - TypeError:“TimeSeriesSplit”对象不可迭代

我正在对具有时间序列拆分的SVR设计进行网格搜索。我的代码是：

from sklearn.svm import SVR
from sklearn.grid_search import GridSearchCV
from sklearn.model_selection import TimeSeriesSplit
from sklearn import svm
from sklearn.preprocessing import MinMaxScaler
from sklearn import preprocessing as pre

X_feature = X_feature.reshape(-1, 1)
y_label = y_label.reshape(-1,1)

param = [{'kernel': ['rbf'], 'gamma': [1e-2, 1e-3, 1e-4, 1e-5],
                       'C': [1, 10, 100, 1000]},
                       {'kernel': ['poly'], 'C': [1, 10, 100, 1000], 'degree': [1, 2, 3, 4]}]


reg = SVR(C=1)
timeseries_split = TimeSeriesSplit(n_splits=3)
clf = GridSearchCV(reg, param, cv=timeseries_split, scoring='neg_mean_squared_error')


X= pre.MinMaxScaler(feature_range=(0,1)).fit(X_feature)

scaled_X = X.transform(X_feature)


y = pre.MinMaxScaler(feature_range=(0,1)).fit(y_label)

scaled_y = y.transform(y_label)



clf.fit(scaled_X,scaled_y )

我的缩放y数据为：

 [0.11321139]
 [0.07218848]
 ...
 [0.64844211]
 [0.4926122 ]
 [0.4030334 ]]

我的缩放X数据是：

[[0.2681013 ]
 [0.03454225]
 [0.02062136]
 ...
 [0.92857565]
 [0.64930691]
 [0.20325924]]

但是，我收到错误消息

TypeError: 'TimeSeriesSplit' object is not iterable

我的回传错误消息是：

  ---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-5-4403e696bf0d> in <module>()
     19
     20
---> 21 clf.fit(scaled_X,scaled_y )

~/anaconda3_501/lib/python3.6/site-packages/sklearn/grid_search.py in fit(self, X, y)
    836
    837         """
--> 838         return self._fit(X, y, ParameterGrid(self.param_grid))
    839
    840

~/anaconda3_501/lib/python3.6/site-packages/sklearn/grid_search.py in _fit(self, X, y, parameter_iterable)
    572                                     self.fit_params, return_parameters=True,
    573                                     error_score=self.error_score)
--> 574                 for parameters in parameter_iterable
    575                 for train, test in cv)
    576

~/anaconda3_501/lib/python3.6/site-packages/sklearn/externals/joblib/parallel.py in __call__(self, iterable)
    777             # was dispatched. In particular this covers the edge
    778             # case of Parallel used with an exhausted iterator.
--> 779             while self.dispatch_one_batch(iterator):
    780                 self._iterating = True
    781             else:

~/anaconda3_501/lib/python3.6/site-packages/sklearn/externals/joblib/parallel.py in dispatch_one_batch(self, iterator)
    618
    619         with self._lock:
--> 620             tasks = BatchedCalls(itertools.islice(iterator, batch_size))
    621             if len(tasks) == 0:
    622                 # No more tasks available in the iterator: tell caller to stop.

~/anaconda3_501/lib/python3.6/site-packages/sklearn/externals/joblib/parallel.py in __init__(self, iterator_slice)
    125
    126     def __init__(self, iterator_slice):
--> 127         self.items = list(iterator_slice)
    128         self._size = len(self.items)
    129

~/anaconda3_501/lib/python3.6/site-packages/sklearn/grid_search.py in <genexpr>(.0)
    573                                     error_score=self.error_score)
    574                 for parameters in parameter_iterable
--> 575                 for train, test in cv)
    576
    577         # Out is a list of triplet: score, estimator, n_test_samples

TypeError: 'TimeSeriesSplit' object is not iterable

我不确定为什么会这样，我怀疑这是在我适合最后一行时发生的。帮助将不胜感激。

最佳答案

首先，您正在使用不兼容的软件包。 grid_search是旧版本，现已弃用，不适用于model_selection。

代替：

from sklearn.grid_search import GridSearchCV

做这个：

from sklearn.model_selection import GridSearchCV

其次，您只需要将TimeSeriesSplit(n_splits=3)发送到cv参数。像这样：

timeseries_split = TimeSeriesSplit(n_splits=3)
clf = GridSearchCV(reg, param, cv=timeseries_split, scoring='neg_mean_squared_error')

无需调用split()。它会在内部由grid_search调用。

关于python - TypeError:“TimeSeriesSplit”对象不可迭代，我们在Stack Overflow上找到一个类似的问题：https://stackoverflow.com/questions/51172889/