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https://github.com/thecrazymage/neural-fca

:interrobang: Interpretable neural networks (neural Formal Concept Analysis).
https://github.com/thecrazymage/neural-fca

fca neural-fca neural-network python

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:interrobang: Interpretable neural networks (neural Formal Concept Analysis).

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# Neural-FCA

This repository is the implementation of a big homework on the course "Ordered Sets in Data Analysis", taught at HSE University in the first semester of the master's program "Data Science" in the fall and winter of 2022.

Course repository on GitHub: [link](https://github.com/EgorDudyrev/OSDA_course).

The topic of my big homework is **neural Formal Concept Analysis (neural FCA)**. Neural FCA repository on GitHub: [link](https://github.com/EgorDudyrev/OSDA_course/tree/Autumn_2022/neural_fca).

## Repository structure

This repository consists of the following main files:
* [**neural_lib.py**](https://github.com/thecrazymage/Neural-FCA/blob/main/source/neural_lib.py) is a library that provides the creation, training, and visualization of interpretable neural networks;
* [**diagnosis.csv**](https://github.com/thecrazymage/Neural-FCA/blob/main/dataset/diagnosis.csv) is the dataset used in this work;
* [**BHW_neural.ipynb**](https://github.com/thecrazymage/Neural-FCA/blob/main/source/BHW_neural.ipynb) is my research;
* [**DWH_neural_report.pdf**](https://github.com/thecrazymage/Neural-FCA/blob/main/docs/DWH_neural_report.pdf) is a detailed progress report;
* [**DWH_neural_presentation.pdf**](https://github.com/thecrazymage/Neural-FCA/blob/main/docs/DWH_neural_presentation.pdf) is a presentation from a big homework defense.