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UNDER CONSTRUCTION

Documentation Status https://img.shields.io/pypi/v/skself PyPI - Python Version

Self-supervised learning sklearn-style

To directly jump into the code look at the sample notebook

Open in Colab

Provides a Model inheriting sklearn.base.BaseEstimator for

Method

Paper

API

Install

Create a new python=3.9 env and install skself from pip

pip install skself

Examples

import skself
... TBD

Usage

All parmeters

import skself
... TBD

Docs

FOR API Reference see

https://sklef.readthedocs.io/en/latest/autoapi/skself/index.html

Cite

If this project helped you during your work: Until a publication is available, please cite as

Tobias Schiele et al. (2023). skself - Self-supervised learning sklearn-style. https://github.com/thetoby9944/skself.

@misc{Schiele2019,
    author = {Tobias Schiele, Daria Kern, Prof. Dr. Ulrich Klauck},
    title = {Skself - Self-supervised learning sklearn-style},
    year = {2022},
    publisher = {GitHub},
    journal = {GitHub repository},
    howpublished = {\url{https://github.com/thetoby9944/skself}},
}

Release files for skself 0.1.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for skself 0.1.0
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Table of built distributions (wheels) for skself 0.1.0
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skself-0.1.0-py3-none-any.whl Python 3 none any Details

Total release size: 45.3 kB

Release files / skself-0.1.0.tar.gz

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