EDITORIAL Editorial I t is a great pleasure and a great honor for me to introduce this new issue of SIGEVOlution that hosts an interview with Stewart W. Wilson. To me, Stewart is a mentor and a great friend. To our community, he is the person who, with XCS and XCSF, singlehandedly revolutionized learning classifier system research. In 1994, his paper on XCS in the Evolutionary Computation Journ...

conclusions by comparing the results of classification using multiple classifier fusion with respect to using each classifier separately, it is found that the classifier fusion is more effective in enhancing the detection accuracy. objectives through the improvement of classification accuracy rate, this work aims to present a computer-assisted diagnosis system for malaria parasite. materials an...

In this work, a system for solving handwritten Arabic word recognition is proposed. The aim is focused on holistic word recognition, which is devoted to recognize averaged size lexicons by using a single classifier. Presently, we investigate the applicability of the Artificial Immune Recognition System (AIRS) to achieve the recognition task. For the feature generation step, ridgelet transform a...

Global features-based methods and local features –based methods have been very successful in face recognition system, yet they can be combined together and jointly optimized so as to minimize the error of a nearest-neighbor classifier. We consider both descriptor for face images with Local Multiple Pattern, and discriminant learning techniques with Exponential Discriminant Analysis. A combinati...

Data mining is a process of discovering useful patterns (knowledge) hidden in extremely large datasets. Classification is a fundamental data mining function, and some other functions can be reduced to it. In this paper we propose a novel classification algorithm (classifier) called MIND (MINing in Databases). MIND can be phrased in such a way that its implementation is very easy using the exten...

potato image segmentation is an important part of image-based potato defect detection. this paper presents a robust potato color image segmentation through a combination of a fuzzy rule based system, an image thresholding based on genetic algorithm (ga) optimization and morphological operators. the proposed potato color image segmentation is robust against variation of background, distance and ...