class sklearn.model_selection.TimeSeriesSplit(n_splits=’warn’, max_train_size=None)
[source]
Time Series cross-validator
Provides train/test indices to split time series data samples that are observed at fixed time intervals, in train/test sets. In each split, test indices must be higher than before, and thus shuffling in cross validator is inappropriate.
This cross-validation object is a variation of KFold
. In the kth split, it returns first k folds as train set and the (k+1)th fold as test set.
Note that unlike standard cross-validation methods, successive training sets are supersets of those that come before them.
Read more in the User Guide.
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The training set has size i * n_samples // (n_splits + 1)
+ n_samples % (n_splits + 1)
in the i``th split,
with a test set of size ``n_samples//(n_splits + 1)
, where n_samples
is the number of samples.
>>> from sklearn.model_selection import TimeSeriesSplit >>> X = np.array([[1, 2], [3, 4], [1, 2], [3, 4], [1, 2], [3, 4]]) >>> y = np.array([1, 2, 3, 4, 5, 6]) >>> tscv = TimeSeriesSplit(n_splits=5) >>> print(tscv) TimeSeriesSplit(max_train_size=None, n_splits=5) >>> for train_index, test_index in tscv.split(X): ... print("TRAIN:", train_index, "TEST:", test_index) ... X_train, X_test = X[train_index], X[test_index] ... y_train, y_test = y[train_index], y[test_index] TRAIN: [0] TEST: [1] TRAIN: [0 1] TEST: [2] TRAIN: [0 1 2] TEST: [3] TRAIN: [0 1 2 3] TEST: [4] TRAIN: [0 1 2 3 4] TEST: [5]
get_n_splits ([X, y, groups]) | Returns the number of splitting iterations in the cross-validator |
split (X[, y, groups]) | Generate indices to split data into training and test set. |
__init__(n_splits=’warn’, max_train_size=None)
[source]
get_n_splits(X=None, y=None, groups=None)
[source]
Returns the number of splitting iterations in the cross-validator
Parameters: |
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Returns: |
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split(X, y=None, groups=None)
[source]
Generate indices to split data into training and test set.
Parameters: |
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Yields: |
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sklearn.model_selection.TimeSeriesSplit
© 2007–2018 The scikit-learn developers
Licensed under the 3-clause BSD License.
http://scikit-learn.org/stable/modules/generated/sklearn.model_selection.TimeSeriesSplit.html