Base classes for sklearn-like parametric objects
Project description
Welcome to skbase
A framework factory for scikit-learn-like and sktime-like parametric objects
skbase
provides base classes for creating scikit-learn-like parametric objects,
along with tools to make it easier to build your own packages that follow these design patterns.
:rocket: Version 0.10.1 is now available. Check out our release notes.
Overview | |
---|---|
CI/CD | |
Code | |
Downloads | |
Citation |
Documentation and Tutorials
To learn more about the package check out:
- our documentation
- our introductory tutorial (jupyter notebooks and video presentation)
:hourglass_flowing_sand: Install skbase
For trouble shooting or more information, see our detailed installation instructions.
- Operating system: macOS X · Linux · Windows 8.1 or higher
- Python version: Python 3.8, 3.9, 3.10, 3.11 and 3.12
- Package managers: pip
pip
skbase releases are available as source packages and binary wheels via PyPI and can be installed using pip. Checkout the full list of pre-compiled wheels on PyPi.
To install the core package use:
pip install scikit-base
or, if you want to install with the maximum set of dependencies, use:
pip install scikit-base[all_extras]
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Hashes for scikit_base-0.10.1-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 0a4c215dc0a6efd17e450d9272e5f4e2edec741cba1a4ac5bed3fb50678451f8 |
|
MD5 | 750d5385c1bbb1962998602488d063f4 |
|
BLAKE2b-256 | cad27f604f422717cc5cddf83baeddbb19d34bb63614678f73f0c445332425cb |