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Time-based k-fold validation splits for heterogeneous data.
Folds plotted on a two-by-two grid. See the examples page for more.
A library for creating time-based cross-validation splits of heterogeneous data, such as raw transaction data with strong non-stationary characteristics.
pandas
, polars
and scikit-learn
.The Time Split application (available here) is designed to help evaluate the effects of different parameters. To start it locally, run
docker run -p 8501:8501 rsundqvist/time-split
or
pip install time-split[app]
python -m time_split app start
in the terminal. You may use
create_explorer_link()
to build application URLs with preselected splitting parameters.
Click here for documentation of the most important types, functions and classes used by the application.
The package is published through the Python Package Index (PyPI). Source code is available on GitHub: https://github.com/rsundqvist/time-split
pip install -U time-split
This is the preferred method to install time-split
, as it will always install the
most recent stable release.
If you don't have pip installed, this Python installation guide can guide you through the process.
Hosted on Read the Docs: https://time-split.readthedocs.io
All contributions, bug reports, bug fixes, documentation improvements, enhancements, and ideas are welcome. To get started, see the Contributing Guide and Code of Conduct.
FAQs
Time-based k-fold validation splits for heterogeneous data.
We found that time-split demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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Socket now supports Scala and Kotlin, bringing AI-powered threat detection to JVM projects with easy manifest generation and fast, accurate scans.
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