Gene Selection with Machine Learning Techniques

This project is an model to compare differents methods of feature selection in the context of microarray gene expression

This project uses the databases of GEMS© 2003-2005, Alexander Statnikov, Constantin F. Aliferis, Ioannis Tsamardinos, Discovery Systems Laboratory, Department of Biomedical Informatics, Vanderbilt University, Nashville, TN, USA The data is avaliable in: http://www.gems-system.org/

Requirements

• python >= 3.65
  • scikit-learn >= 0.20
  • deap >= 1.2.2

How to use

You can use the follow command to use the default databases:

./run.sh

This will create three log files with the results

Or, if you want to run on an specific database, try the follow command:

python3 main.py MY_DATABASE.txt 2>/dev/null

If you want to see the relevant genes selected, change the argument VIEW_SELECTED_GENES in the file main.py