A Dash application that uses data mining algorithms (KMeans, DBscan clustering) to analyses the whole space of answer sets, identifies the inner patterns, and helps users to find the interesting attributes for further investigation.
Python 3.6 or later version
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.
First create a virtual environment with conda or venv inside a temp folder, then activate it.
virtualenv venv
# Windows
venv\Scripts\activate
# Or Linux
source venv/bin/activate
Clone the git repo
git clone https://github.com/Lexise/ASP-Analysis
To install all of the required packages to your virtual environment, simply run:
pip install -r requirements.txt
Run the app
python app.py
If you want to process your own data, it should be named in the way that end with ".apx" for arguments ans ".EE-PR" for answer sets. For example:
- Dash - Main server and interactive components
- Plotly Python - Used to create the interactive plots
The following are screenshots for the app in this repo:
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Inspiration
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Academic usage