This paper investigates the impact of geometric semantic crossover operators in a wide range of symbolic regression problems. First, it analyses the impact of using Manhattan and Euclidean distance geometric semantic crossovers in the learning …
This work borrows the traditional Pittsburgh-style representation from Genetic-Based Machine Learning and evaluates its performance in artificial immune systems (AIS) for classification. Our main goal is to select as few instances as possible to …
This study proposes a new algorithm for supervised learning, based on the clonal selection principle exhibited in natural and artificial immune systems. The method, called Clonal Selection Classifier with Data Reduction (CSCDR), utilizes a fitness …
This work presents a technique based on artificial immune system (AIS) for MR brain image classification. The method is an approach based on real-valued negative selection (RNS) algorithm and the use of a genetic algorithm to find a good combination …
This work presents a classification technique based on artificial immune system (AIS). The method consists of a modification of the real-valued negative selection (RNS) algorithm for pattern recognition. Our approach considers a modification in two …