| Title | The influence of the risk functional in data classification with MLPs |
| Publication Type | Book |
| Year of Publication | 2008 |
| Authors | Silva, LM, Embrechts, M, Santos, JM, De Sá, JM |
| Series Title | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)Lect. Notes Comput. Sci. |
| Volume | 5163 LNCS |
| Number of Pages | 185 - 194 |
| City | Prague |
| ISBN Number | 03029743 (ISSN); 3540875352 (ISBN); 9783540875352 (ISBN) |
| Keywords | Backpropagation, Complex mapping, Data classification, Data sets, Electric loads, Experiments, Functionals, Minimum probability of error, MLP classifiers, Multi layer perceptron, Multi-layer perceptrons, Multilayer neural networks, Multilayers, Optimal performance, Pattern recognition systems, Probability density function, risks, Statistical analysis, Weighted distance |
| Abstract | We investigate the capability of multilayer perceptrons using specific risk functionals attaining the minimum probability of error (optimal performance) achievable by the class of mappings implemented by the multilayer perceptron (MLP). For that purpose we have carried out a large set of experiments using different risk functionals and datasets. The experiments were rigorously controlled so that any performance difference could only be attributed to the different risk functional being used. Statistical analysis was also conducted in a careful way. From the several conclusions that can be drawn from our experimental results it is worth to emphasize that a risk functional based on a specially tuned exponentially weighted distance attained the best performance in a large variety of datasets. As to the issue of attaining the minimum probability of error we also carried out classification experiments using non-MLP classifiers that implement complex mappings and are known to provide the best results until this date. These experiments have provided evidence that at least in many cases, by using an adequate risk functional, it will be possible to reach the optimal performance. © Springer-Verlag Berlin Heidelberg 2008. |
| URL | http://www.scopus.com/inward/record.url?eid=2-s2.0-58849129862&partnerID=40&md5=d9d0d90a540a21b191eebbf1956ed6e9 |
