Present paper demonstrates the success of a new evolutionary
approach to support vector machines on the discovery of linear separating
hyperplanes for separable and nonseparable data. An evolutionary
algorithm is appointed to determine the optimal linear separating hyperplane
between binary classes. Experiments prove the success of the new
approach in determining linear decision surfaces.