MLROSe: Machine Learning, Randomized Optimization and Search
Project description
mlrose: Machine Learning, Randomized Optimization and SEarch - README
This repository contains the source code for the mlrose Python package. This package implements a range of Machine Learning, Randomized Optimization and SEarch algorithms, to allow users to explore the properties of these algorithms under various conditions.
Installation
mlrose was written in Python 3 and requires NumPy, SciPy and Scikit-Learn (sklearn).
The latest released version is available at the Python package index < insert link to PyPi page> and can be installed using pip
:
pip install mlrose
Project Background
Main Features
Documentation
The official mlrose documentation can be found here:
Licensing, Authors, Acknowledgements
mlrose was written by Genevieve Hayes and is distributed under the 3-Clause BSD license.
You can cite mlrose in research publications and reports as follows:
- Hayes, G. (2018). mlrose: Machine Learning, Randomized Optimization and SEarch package for Python. https://github.com/gkhayes/mlrose. Accessed: day month year.
BibTeX entry:
@misc{Hayes18,
author = {Hayes, G},
title = {{mlrose: Machine Learning, Randomized Optimization and SEarch package for Python}},
year = 2018,
howpublished = {\url{https://github.com/gkhayes/mlrose}},
note = {Accessed: day month year}
}
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.