https://github.com/firefly-cpp/uarmsolver
universal Association Rule Mining Solver
https://github.com/firefly-cpp/uarmsolver
association-rule-mining data-mining data-science evolutionary-algorithms swarm-intelligence
Last synced: 2 months ago
JSON representation
universal Association Rule Mining Solver
- Host: GitHub
- URL: https://github.com/firefly-cpp/uarmsolver
- Owner: firefly-cpp
- License: mit
- Created: 2020-09-15T09:54:37.000Z (almost 5 years ago)
- Default Branch: master
- Last Pushed: 2025-03-03T16:54:43.000Z (4 months ago)
- Last Synced: 2025-03-27T00:54:57.297Z (3 months ago)
- Topics: association-rule-mining, data-mining, data-science, evolutionary-algorithms, swarm-intelligence
- Language: C++
- Homepage:
- Size: 895 KB
- Stars: 14
- Watchers: 2
- Forks: 12
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
Awesome Lists containing this project
README
uARMSolver
universal Association Rule Mining Solver
🛠️ Compiling •
📦 Installation •
🚀 Example •
🐳 Docker •
📝 References •
📄 Cite us •
🔑 License •
🫂 Contributors
The framework is written fully in C++ and runs on all platforms. 🖥️ It allows users to preprocess their data in a transaction database, to make discretization of data, to search for association rules and to guide a presentation/visualization of the best rules found using external tools. 📊 As opposed to the existing software packages or frameworks, this also supports numerical and real-valued types of attributes besides the categorical ones. Mining the association rules is defined as an optimization and solved using the nature-inspired algorithms that can be incorporated easily. 🌿 Because the algorithms normally discover a huge amount of association rules, the framework enables a modular inclusion of so-called visual guiders for extracting the knowledge hidden in data, and visualize these using external tools. 🔍
## 🛠️ Compiling
make
## 📦 Installation
To install `uARMSolver` on Fedora, use:
```sh
$ dnf install uARMSolver
```
To install `uARMSolver` on RHEL, CentOS, Scientific Linux enable EPEL 8 and use:
```sh
$ dnf install uARMSolver
```
To install `uARMSolver` on [Arch-based distributions](https://wiki.archlinux.org/title/Arch-based_distributions#Active), use an [AUR helper](https://wiki.archlinux.org/title/AUR_helpers):
```sh
$ yay -Syyu uarmsolver
```
To install `uARMSolver` on Alpine Linux, enable Community repository and use:
```sh
$ apk add uarmsolver
```
To install `uARMSolver` on Windows, follow to the [following instructions](WINDOWS_INSTALLATION.md).
## 🚀 Example
./uARMSolver -s arm.set
arm.set is a problem definition file. Check [README](bin/README.txt) for more details about the format of .set file.
## 🐳 Docker
If you prefer to use a Docker container for running `uARMSolver`, you can use the `uarmsolver-container` repository. This repository provides a Docker setup for running `uARMSolver`.
### uARMSolver Container 📦
The `uarmsolver-container` repository contains a Docker container setup for running `uARMSolver`. You can find it here: [uarmsolver-container](https://github.com/firefly-cpp/uarmsolver-container).
To build and run the Docker container, follow the instructions in the [uarmsolver-container README](https://github.com/firefly-cpp/uarmsolver-container#readme).
## 📝 References:
[1] I. Fister Jr., A. Iglesias, A. Gálvez, J. Del Ser, E. Osaba, I Fister. [Differential evolution for association rule mining using categorical and numerical attributes](http://www.iztok-jr-fister.eu/static/publications/231.pdf) In: Intelligent data engineering and automated learning - IDEAL 2018, pp. 79-88, 2018.
[2] I. Fister Jr., I Fister. Information cartography in association rule mining. arXiv preprint [arXiv:2003.00348](https://arxiv.org/abs/2003.00348), 2020.
[3] I. Fister Jr., V. Podgorelec, I. Fister. [Improved Nature-Inspired Algorithms for Numeric Association Rule Mining](https://link.springer.com/chapter/10.1007/978-3-030-68154-8_19). In: Vasant P., Zelinka I., Weber GW. (eds) Intelligent Computing and Optimization. ICO 2020. Advances in Intelligent Systems and Computing, vol 1324. Springer, Cham.
## 📄 Cite us
I. Fister, I Fister Jr. uARMSolver: A framework for Association Rule Mining. arXiv preprint [arXiv:2010.10884](https://arxiv.org/abs/2010.10884), 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!
## 🫂 Contributors
Iztok Fister, Iztok Fister Jr.