TSCV: Time Series Cross-Validation

This repository is a scikit-learn extension for time series cross-validation.
It introduces gaps between the training set and the test set, which mitigates the temporal dependence of time series and prevents information leakage.

Installation

bashCopy
pip install tscv

or

bashCopy
conda install -c conda-forge tscv

Usage

This extension defines 3 cross-validator classes and 1 function:

• GapLeavePOut
• GapKFold
• GapRollForward
• gap_train_test_split

The three classes can all be passed, as the cv argument, to
scikit-learn functions such as cross-validate, cross_val_score,
and cross_val_predict, just like the native cross-validator classes.

The one function is an alternative to the train_test_split function in scikit-learn.

Examples

The following example uses GapKFold instead of KFold as the cross-validator.

pythonCopy
import numpy as np
from sklearn import datasets
from sklearn import svm
from sklearn.model_selection import cross_val_score
from tscv import GapKFold

iris = datasets.load_iris()
clf = svm.SVC(kernel='linear', C=1)

# use GapKFold as the cross-validator
cv = GapKFold(n_splits=5, gap_before=5, gap_after=5)
scores = cross_val_score(clf, iris.data, iris.target, cv=cv)

The following example uses gap_train_test_split to split the data set into the training set and the test set.

pythonCopy
import numpy as np
from tscv import gap_train_test_split

X, y = np.arange(20).reshape((10, 2)), np.arange(10)
X_train, X_test, y_train, y_test = gap_train_test_split(X, y, test_size=2, gap_size=2)

Contributing

• Report bugs in the issue tracker
• Express your use cases in the issue tracker

Documentations

• tscv.readthedocs.io

Acknowledgments

• I would like to thank Jeffrey Racine and Christoph Bergmeir for the helpful discussion.

License

BSD-3-Clause

Citation

Wenjie Zheng. (2021). Time Series Cross-Validation (TSCV): an extension for scikit-learn. Zenodo. http://doi.org/10.5281/zenodo.4707309

latexCopy
@software{zheng_2021_4707309,
  title={{Time Series Cross-Validation (TSCV): an extension for scikit-learn}},
  author={Zheng, Wenjie},
  month={april},
  year={2021},
  publisher={Zenodo},
  doi={10.5281/zenodo.4707309},
  url={http://doi.org/10.5281/zenodo.4707309}
}