| Issue |
ITM Web Conf.
Volume 59, 2024
II International Workshop “Hybrid Methods of Modeling and Optimization in Complex Systems” (HMMOCS-II 2023)
|
|
|---|---|---|
| Article Number | 02020 | |
| Number of page(s) | 11 | |
| Section | Interdisciplinary Mathematical Modeling and Applications | |
| DOI | https://doi.org/10.1051/itmconf/20245902020 | |
| Published online | 25 January 2024 | |
Thefittest: evolutionary machine learning in Python
Artificial Intelligence Laboratory, Siberian Federal University,
Krasnoyarsk,
Russia
* Corresponding author: sherstpasha99@gmail.com
Thefittest is a new Python library specializing in evolutionary optimization methods and machine learning methods that use evolutionary optimization methods. Thefittest provides both classical evolutionary algorithms and efficient modifications of these algorithms that do not have implementations in the open access. Among the advantages of the library are the performance of the implemented methods, accessibility and ease of use. The paper discusses the motivation for developing and leading the project, describes the structure of the library with examples of use, and provides a comparison with other projects with a similar development goal. Thefittest is an open-source project published on GitHub and PyPi, developed using modern methods of code analysis and testing. At the moment of writing the paper, the latest version of the library is 0.2.3.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.