https://github.com/firefly-cpp/niaclass

https://github.com/firefly-cpp/niaclass

Last synced: 6 months ago
JSON representation

• Host: GitHub
• URL: https://github.com/firefly-cpp/niaclass
• Owner: firefly-cpp
• License: mit
• Created: 2021-02-02T20:12:43.000Z (over 4 years ago)
• Default Branch: master
• Last Pushed: 2024-12-05T15:42:34.000Z (7 months ago)
• Last Synced: 2024-12-05T16:36:06.316Z (7 months ago)
• Language: Python
• Size: 249 KB
• Stars: 0
• Watchers: 2
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • Changelog: CHANGELOG.md
  • Contributing: docs/contributing.rst
  • License: LICENSE
  • Code of conduct: CODE_OF_CONDUCT.md
  • Citation: CITATION.cff

Awesome Lists containing this project

README

        


    





    

        

    

    

    

    

        

    





    

    

        

    

    

        

    

    





    📦 Installation •

    ✨ Functionalities •

    🚀 Examples •

    📝 Reference papers •

    🔑 License •

    📄 Cite us



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

To install NiaClass with pip3, use:

```sh

pip3 install niaclass

```

In case you would like to try out the latest pre-release version of the framework, install it using:

```sh

pip3 install niaclass --pre

```

### Fedora Linux

To install NiaClass on Fedora, use:

```sh

$ dnf install python-niaclass

```

## ✨ Functionalities

- Binary classification,

- Multi-class classification,

- Support for numerical and categorical features.

## 🚀 Examples

Usage examples can be found [here](examples).

## 📝 Reference papers

[1] Iztok Fister Jr., Iztok Fister, Dušan Fister, Grega Vrbančič, Vili Podgorelec. [On the potential of the nature-inspired algorithms for pure binary classification](http://www.iztok-jr-fister.eu/static/publications/267.pdf). In. Computational science - ICCS 2020 : 20th International Conference, Proceedings. Part V. Cham: Springer, pp. 18-28. Lecture notes in computer science, 12141, 2020

## 🔑 License

This package is distributed under the MIT License. This license can be found online at .

## 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](https://iztok-jr-fister.eu/static/publications/291.pdf). In: Tan Y., Shi Y. (eds) Advances in Swarm Intelligence. ICSI 2021. Lecture Notes in Computer Science, vol 12690. Springer, Cham.