Metadata-Version: 2.1
Name: scikit-physlearn
Version: 0.1.4
Summary: A Python package for single-target and multi-target regression tasks.
Home-page: https://github.com/a-wozniakowski/scikit-physlearn
Maintainer: Alex Wozniakowski
Maintainer-email: wozn0001@e.ntu.edu.sg
License: MIT
Download-URL: https://github.com/a-wozniakowski/scikit-physlearn
Project-URL: Paper, https://arxiv.org/abs/2005.06194
Platform: UNKNOWN
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Classifier: Programming Language :: Python
Classifier: Topic :: Software Development
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX
Classifier: Operating System :: Unix
Classifier: Operating System :: MacOS
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Description-Content-Type: text/x-rst
Requires-Dist: numpy (>=1.13.3)
Requires-Dist: scipy (>=0.19.1)
Requires-Dist: scikit-learn (>=0.23.0)
Requires-Dist: pandas (>=1.0.0)
Requires-Dist: shap (>=0.36.0)
Requires-Dist: ipython (>=7.11.0)
Requires-Dist: bayesian-optimization (>=1.2.0)
Requires-Dist: catboost (>=0.23.2)
Requires-Dist: xgboost (>=1.2.0)
Requires-Dist: lightgbm (>=2.3.0)
Requires-Dist: mlxtend (>=0.17.0)
Requires-Dist: joblib (>=0.11)
Requires-Dist: python-levenshtein-wheels (>=0.13.1)
Provides-Extra: docs
Requires-Dist: sphinx (>=3.0.3) ; extra == 'docs'
Requires-Dist: sphinx-gallery (>=0.7.0) ; extra == 'docs'
Provides-Extra: tests

.. -*- mode: rst -*-

|SOTA|_ |DOCS|_ |PyPI|_

.. |SOTA| image:: https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/boosting-on-the-shoulders-of-giants-in/multi-target-regression-on-google-5-qubit
.. _SOTA: https://paperswithcode.com/sota/multi-target-regression-on-google-5-qubit?p=boosting-on-the-shoulders-of-giants-in

.. |DOCS| image:: https://readthedocs.org/projects/scikit-physlearn/badge/?version=latest
.. _DOCS: https://scikit-physlearn.readthedocs.io/en/latest/?badge=latest

.. |PyPI| image:: https://badge.fury.io/py/scikit-physlearn.svg
.. _PyPI: https://badge.fury.io/py/scikit-physlearn

################
Scikit-physlearn
################

**Scikit-physlearn** is a machine learning library designed to amalgamate 
`Scikit-learn <https://scikit-learn.org/>`_,
`LightGBM <https://lightgbm.readthedocs.io/en/latest/index.html>`_,
`XGBoost <https://xgboost.readthedocs.io/en/latest/>`_,
`CatBoost <https://catboost.ai/>`_,
and `Mlxtend <http://rasbt.github.io/mlxtend/>`_ 
regressors into a flexible framework that:

- Follows the Scikit-learn API.
- Processes pandas data representations.
- Solves single-target and multi-target regression tasks.
- Interprets regressors with `SHAP <https://shap.readthedocs.io/en/latest/>`_.

Additionally, the library contains the official implementation of
`base boosting <https://arxiv.org/abs/2005.06194>`_, which is an algorithmic
paradigm for building additive expansions based upon the output of any
base-level regressor. The implementation:

- Supplants the statistical initialization in gradient boosting
  with the output of any base-level regressor.
- Boosts arbitrary basis functions, i.e., it is not limited to boosting
  decision trees.
- Efficiently learns in the low data regime.

The `library <https://github.com/a-wozniakowski/scikit-physlearn>`_ was
started by Alex Wozniakowski during his graduate studies at Nanyang Technological
University.

************
Installation
************

Scikit-physlearn can be installed from `PyPI <https://pypi.org/project/scikit-physlearn/>`__::

    pip install scikit-physlearn

To build from source, see the `installation guide <https://scikit-physlearn.readthedocs.io/en/latest/install.html>`_.

********
Citation
********

If you use this library, please consider adding the corresponding citation:

.. code-block:: latex

    @article{wozniakowski_2020_boosting,
      title={Boosting on the shoulders of giants in quantum device calibration},
      author={Wozniakowski, Alex and Thompson, Jayne and Gu, Mile and Binder, Felix C.},
      journal={arXiv preprint arXiv:2005.06194},
      year={2020}
    }


