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Prototype based classifiers allow to determine the class of a new example based on a reduced set of prototypes instead of using a large set of known samples. By doing this, the computational time gets substantially decreased as the initial set is replaced by a reduced one and hence the classification requires less computations to estimate nearest neighbours. In most simple classification problems...
As an important branch of Knowledge Discovery, the task of Data Classification is to determine the objects that belong to which pre-defined goals. As evolutionary computation does not require priori assumptions, it shows great vitality in dealing with imprecise, incomplete and uncertain information, which the traditional methods of statistical classifications are helpless in the classification issues...
Gene expression programming (GEP) is a kind of genotype/phenotype based genetic algorithm. Its successful application in classification rules mining has gained wide interest in data mining and evolutionary computation fields. However, current GEP based classifiers represent classification rules in the form of expression tree, which is less meaningful and expressive than decision tree. What's more,...
Soft computing is gradually opening up several possibilities in bioinformatics, especially by generating low-cost, low-precision (approximate), good solutions. In this paper, we survey the role of different soft computing paradigms, like fuzzy sets (FSs), artificial neural networks (ANNs), evolutionary computation, rough sets (RSes), and support vector machines (SVMs), in this direction. The major...
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