Python framework for building classifiers using nature-inspired algorithms
Project description
NiaClass is a framework for solving classification tasks using nature-inspired algorithms. The framework is written fully in Python. Its goal is to find the best possible set of classification rules for the input data using the NiaPy framework, which is a popular Python collection of nature-inspired algorithms. The NiaClass classifier supports numerical and categorical features.
- Free software: MIT license,
- Documentation: https://niaclass.readthedocs.io/en/latest/,
- Python versions: 3.7.x, 3.8.x, 3.9.x.
Installation
pip3
Install NiaClass with pip3:
pip3 install niaclass
In case you would like to try out the latest pre-release version of the framework, install it using:
pip3 install niaclass --pre
Fedora Linux
To install NiaClass on Fedora, use:
$ dnf install python-niaclass
Functionalities
- Binary classification,
- Multi-class classification,
- Support for numerical and categorical features.
Examples
Usage examples can be found here.
Reference Papers (software is based on ideas from):
[1] Iztok Fister Jr., Iztok Fister, Dušan Fister, Grega Vrbančič, Vili Podgorelec. On the potential of the nature-inspired algorithms for pure binary classification. In. Computational science - ICCS 2020 : 20th International Conference, Proceedings. Part V. Cham: Springer, pp. 18-28. Lecture notes in computer science, 12141, 2020
Licence
This package is distributed under the MIT License. This license can be found online at http://www.opensource.org/licenses/MIT.
Disclaimer
This framework is provided as-is, and there are no guarantees that it fits your purposes or that it is bug-free. Use it at your own risk!
Cite us
Pečnik L., Fister I., Fister Jr. I. (2021) NiaClass: Building Rule-Based Classification Models Using Nature-Inspired Algorithms. In: Tan Y., Shi Y. (eds) Advances in Swarm Intelligence. ICSI 2021. Lecture Notes in Computer Science, vol 12690. Springer, Cham.
Project details
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