Subgroup discovery is a descriptive data mining technique using supervised learning. This
paper presents a summary about the main properties and elements about subgroup discovery task.
In addition, we will focus on the suitability and potential of the search performed by evolutionary
algorithms in order to apply in the development of subgroup discovery algorithms, and in the use
of fuzzy logic which is a soft computing technique very close to the human reasoning. The
hybridisation of both techniques are well known as evolutionary fuzzy system.
The most relevant applications of evolutionary fuzzy systems for subgroup discovery in the
bioinformatics domains are outlined in this work. Specifically, these algorithms are applied to a
problem based on the Influenza A virus and the accute sore throat problem
