COVID-19 Data Analysis with Multi-objective Evolutionary Algorithm for Causal Association Rules Mining

Supplementary Material for article COVID-19 Data Analysis with Multi-objective Evolutionary Algorithm for Causal Association Rules Mining in Mathematical and Computational Applications journal, Special Issue "Evolutionary Multi-objective Optimization: An Honorary Issue Dedicated to Professor Kalyanmoy Deb"

Authors: Santiago Sinisterra-Sierra [1], Salvador Godoy-Calderón [1] and Miriam Pescador-Rojas [2]

[1] Centro de Investigación en Computación, Instituto Politécnico Nacional, Ciudad de México, México; [2] Escuela Superior de Cómputo, Instituto Politécnico Nacional, Ciudad de México, México.

Installation

Make sure to install Python 3.9 through anaconda. Then, run pip install -r requirements.txt to install the required Python dependencies.

This implementation uses Clickhouse tables in a local instance. Check https://clickhouse.com/docs/en/install/ for details on how to install Clickhouse.

Rule results are cached in a redis database deployed with Docker. Please install docker and docker-compose, then cd redis_cache && docker-compose up to start Redis.

Running the algorithm

Run python main.py to execute the algorithm. Each run creates a new folder named with the timestamp of the execution. The file selection.csv contains the results of the algorithm. For further exploration of more evaluation measures, finals.csv contains all the possible evaluation measures considered by the algorithm.