A Modified Genetic Algorithm for Training the Standard Support Vector Machine

Provided by: American V-King Scientific Publishing
Topic: Cloud
Format: PDF
The Standard Problem (SP) for Support Vector Machines (SVMs), proposed by the researcher, is a non-convex nonlinear programming problem, and the general optimization methods in training the SP may obtain a local optimal solution. In order to avoid the local optimal solution, this paper utilizes a kind of Modified Genetic Algorithm (MGA) to search the global optimal solution of the SP. At the same time, the MGA fully exploits the superiority and characteristic of the SP, which indicates that the authors' method is effective and feasible. Some numerical experiments are also given, which illustrate that their genetic algorithm is effective.

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