Name
Abstract | ||
|---|---|---|
Referring to the statistical point of view, we present in this work, a new criterion for evaluating neural networks stability compared to the Bayesian classifier. The stability comparison is performed by the error rate probability densities function estimated by the kernel-diffeomorphism semi-bounded Plug-in algorithm. The Bayesian and combination approaches for neural networks improve the performance and stability degree of the classical neural classifiers. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/ICIP.2014.7025876 | ICIP |
Keywords | Field | DocType |
stability,combination | Intelligent control,Pattern recognition,Naive Bayes classifier,Computer science,Word error rate,Types of artificial neural networks,Artificial intelligence,Bayesian neural networks,Artificial neural network,Machine learning,Kernel (statistics),Bayesian probability | Conference |
ISSN | Citations | PageRank |
1522-4880 | 0 | 0.34 |
References | Authors | |
8 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ibtissem Ben Othman | 1 | 0 | 1.01 |
| Faouzi Ghorbel | 2 | 361 | 46.48 |