Time-based k-fold validation splits for heterogeneous data.
Project description
Time Split
Time-based k-fold validation splits for heterogeneous data.
Folds plotted on a two-by-two grid. See the examples page for more.
What is it?
A library for creating time-based cross-validation splits of heterogeneous data, such as raw transaction data with strong non-stationary characteristics.
Highlighted Features
- Splitting schedules based on a fixed interval, a CRON-expression, or a pre-defined list.
- Data selection based on a timedelta, or the splitting schedule itself.
- Automatically extract and normalize data limits for supported data types.
- Plotting function for visualization of folds. Display fold sizes (hour/row count), or use custom text.
- Integrations for popular
libraries such as
pandas,polarsandscikit-learn. - Convenient web application for exploring folds with different parameters.
Experimenting with parameters
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.
Installation
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.
License
Documentation
Hosted on Read the Docs: https://time-split.readthedocs.io
Contributing
All contributions, bug reports, bug fixes, documentation improvements, enhancements, and ideas are welcome. To get started, see the Contributing Guide and Code of Conduct.
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