Concerning the potential of evolutionary support vector machines

— Within the present paper, we put forward a novel hybridization between support vector machines and evolutionary algorithms. Evolutionary support vector machines consider the classification task as in support vector machines but use an evolutionary algorithm to solve the optimization problem of determining the decision function. They can explicitly acquire the coefficients of the separating hyperplane, which is often not possible within the classical technique. More important, evolutionary support vector machines obtain the coefficients directly from the evolutionary algorithm and can refer them at any point during a run. In addition, they do not require properties of positive (semi-)definition for kernels within nonlinear learning. The concept can be furthermore extended to handle large amounts of data, a problem frequently occurring e.g. in spam mail detection, one of our test cases. An adapted chunking technique is therefore alternatively used. In addition to two different re...

• Type: Conference
• Year: 2007
• Where: CEC
• Authors: Ruxandra Stoean, Mike Preuss, Catalin Stoean, Dumitru Dumitrescu
• Keywords: Artificial Intelligence, CEC 2007, Evolutionary Algorithm, Evolutionary Support Vector, Support Vector Machines