Γενετικός Αλγόριθμος Ταξινόμησης Genetic AIRS
This thesis presents an hybrid classification method based on one hand on theories and principles of Artificial Immune Systems and on the other hand on Genetic Algorithm techniques. The inspiration came from AIRS algorithm(Artificial Immune Resource System), one of the most accurate classification algorithms, and from Genetic Algorithm methods, so we developed one hybrid algorithm Genetic AIRS. Next, we investigated the behavior of the algorithm created, with respect to the AIRS algorithm and present the advantages and disadvatages. The main difference of these two algorithms beside the fact of different implementation is the fact that AIRS executes topically and Genetic AIRS spherically. The first part of this thesis is the theoritical base of the algorithm and the second part is the application on various data sets.