An Experimental Comparison of MLP Training Methods

This chapter is dedicated to presenting a detailed analysis of the performance of first- and second-order training algorithms when applied to a range of benchmark training tasks. The chapter is in three main sections: Section 5.1 gives details of the chosen benchmark tasks; Section 5.2 provides a detailed description of the architectures, training algorithms and parameter settings used in the tests; and Section 5.3 presents an analysis of the test results in terms of training speed and ‘global reliability’. The training data are reproduced in tabulated form in the Appendix.