Towards a modeling framework for integrating hybrid techniques

Nowadays, it is easy to find a number of different hybrid approaches for fuzzy modeling. All these approaches were built in a very ad-hoc manner, and did not follow a systematic approach. However, we think that some kind of information system which helps in the study of how algorithms can combine to model systems in a fuzzy fashion should be very helpful. In this article, we propose METALA (META-Learning Architecture), an architecture to study the typical processes of machine learning, to study the particular issue of fuzzy modeling.