https://github.com/ilvondir/lem2
Implementation of LEM2 inference rule algorithm created with Python.
https://github.com/ilvondir/lem2
inference-rules lem2 rough-sets
Last synced: 13 days ago
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Implementation of LEM2 inference rule algorithm created with Python.
- Host: GitHub
- URL: https://github.com/ilvondir/lem2
- Owner: Ilvondir
- Created: 2024-06-24T19:49:15.000Z (10 months ago)
- Default Branch: master
- Last Pushed: 2025-02-04T19:55:08.000Z (3 months ago)
- Last Synced: 2025-02-04T20:33:44.479Z (3 months ago)
- Topics: inference-rules, lem2, rough-sets
- Language: Python
- Homepage:
- Size: 476 KB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# LEM2
The implementation of the LEM2 algorithm (*Learning from Examples Module, version 2*), a greedy machine learning algorithm used in classification problems. It is based on the theory of rough sets and works by generating a minimal covering of decision rules for each label in the training data.
The implementation allows the algorithm to run in various debugging modes using the `verbose` parameter. Additionally, there is an option to choose whether the algorithm should generate only certain rules or also uncertain ones, using the `only_certain` parameter.
Due to the fact that the LEM2 algorithm works only with discretized data, a simple discretizer has also been implemented. Its operation is based on dividing the range of a given attribute into a selected number of sets, which represent discrete value.
The proposed implementation was developed in Python and tested on several different binary classification problems.
## Used Tools
- Python 3.11.2
- Pandas 2.2.3
- Matplotlib 3.10.0
- Numpy 2.2.0
## Requirements
For running the application you need:
- [Python](https://www.python.org/downloads/)
## How to run
1. Execute command `git clone https://github.com/Ilvondir/lem2`.
2. Install required packages by `pip install -r requirements.txt`.
3. Check the implementation in `lem2.py`, its tests and documentations in `html` files.