Data Classification Using Support Vector Machines Trained with Evolutionary Algorithms Employing Kernel Adatron
Chapter 2 presents an approach to perform large-scale data classification using Support Vector Machines (SVM), trained using Kernel-Adatron (KA) algorithm, combined with Artificial Bee Colony (ABC), micro-Artificial Bee Colony (μABC), Differential Evolution (DE), and Particle Swarm Optimization (PSO). The combination of KA and bio-inspired algorithms allows us to obtain a parallelized system of classification that may be effectively applied to solve pattern recognition with data of large dimension, keeping its computational complexity lower than previous large scale classifiers that use SVM. Our proposed SVM-bio-inspired ...
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