.. ml_uncertainty documentation master file, created by
   sphinx-quickstart on Tue Jun 13 15:06:56 2017.
   You can adapt this file completely to your liking, but it should at least
   contain the root `toctree` directive.
   
.. currentmodule:: ml_uncertainty

Machine Learning Uncertainty Estimation Toolbox
===============================================

`David A. Sheen <mailto:david.sheen@nist.gov>`_

*National Institute of Standards and Technology*

*Last Revision* |today|

`Download this software from GitHub <https://github.com/usnistgov/ml_uncertainty_py>`_

Welcome to the home page for the Machine Learning Uncertainty Toolbox. This software is a Python package that calculates uncertainties in machine learning models using bootstrapping and residual bootstrapping. It is intended to interface with scikit-learn but any Python package that uses a similar interface should work.


Contents
++++++++

.. toctree::
   :maxdepth: 2
   :caption: Contents:
   
   docs
   toy_regression_object-oriented
   toy_regression_object-oriented_2nd_order
   qsar_regression_object-oriented
   run_environmental_pls-Copy1
   

Legal
+++++

This software is subject to the `NIST Software License <https://www.nist.gov/director/licensing>`_ (revised as of August 2018).


Contact
+++++++

David Sheen 

* `Email <mailto:david.sheen@nist.gov>`_
* `NIST Staff Page <https://www.nist.gov/people/david-sheen>`_
* `GitHub profile <https://github.com/davidasheen>`_

Links
+++++

`NIST GitHub Organization <https://github.com/usnistgov>`_

`NIST MetQual program <https://www.nist.gov/programs-projects/metabolomics-quality-assurance-and-quality-control-materials-metqual-program>`_

`NIST Chemical Informatics Research Group <https://www.nist.gov/mml/csd/chemical-informatics-research-group>`_

`NIST home page <http://nist.gov>`_

Indices and tables
==================

* :ref:`genindex`
* :ref:`modindex`
* :ref:`search`