Demonstrates propositions of supervised machine learning theories
Project description
smltheory
Demonstrates propositions of supervised machine learning theories.
Installation
$ pip install smltheory
Usage
smltheory can be used to demonstrate propositions of
supervised machine learning theories. Specifically, the functions
demonstrate the propositions of excess risk decomposition
and the bias-variance tradeoff.
For a demonstration of each supervised machine learning proposition, see whitepaper.
Contributing
Interested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.
License
smltheory was created by Sebastian Sciarra. It is licensed under the terms of the MIT license.
Credits
smltheory was created with cookiecutter and the py-pkgs-cookiecutter template.
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