| Title | Bounds for the Average Generalization Error of the Mixture of Experts Neural Network |
| Publication Type | Book |
| Year of Publication | 2004 |
| Authors | Alexandre, LA, Campilho, A, Kamel, M |
| Series Title | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)Lect. Notes Comput. Sci. |
| Volume | 3138 |
| Number of Pages | 618 - 625 |
| ISBN Number | 03029743 (ISSN) |
| Keywords | Generalization error bounds, Mixture of experts, Modular neural networks |
| Abstract | In this paper we derive an upper bound for the average-case generalization error of the mixture of experts modular neural network, based on an average-case generalization error bound for an isolated neural network. By doing this we also generalize a previous bound for this architecture that was restricted to special problems. We also present a correction factor for the original average generalization error, that was empirically obtained, that yields more accurate error bounds for the 6 data sets used in the experiments. These experiments illustrate the validity of the derived error bound for the mixture of experts modular neural network and show how it can be used in practice. © Springer-Verlag 2004. |
| URL | http://www.scopus.com/inward/record.url?eid=2-s2.0-35048839786&partnerID=40&md5=10183183d399e4055c331416faef909e |
