Titlebook: Support Vector Machines and Evolutionary Algorithms for Classification; Single or Together? Catalin Stoean,Ruxandra Stoean Book 2014 Spring

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Introduction,SVMs) are known to be a smart choice. But how can one make a personal, more flexible implementation of the learning engine that makes them run that well? And how does one open the black box behind their predicted diagnosis and explain the reasoning to the otherwise reluctant fellow physicians? Alter

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Support Vector Learning and Optimizationarning within both the theoretical and red practical research environments. This very performing technique suffers nevertheless from the curse of an opaque engine [Huysmans et al, 2006], which is undesirable for both theoreticians, who are keen to control the modeling, and the practitioners, who are

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Genetic Chromodynamicsles. Such vectors of thresholds will be constructed for each class of the problem and we will further refer to them as prototypes. They will efficiently represent the class distributions and therefore well discriminate objects of different labels.