Name
Title | ||
|---|---|---|
Towards a framework for multiple artificial neural network topologies validation by means of statistics |
Abstract | ||
|---|---|---|
AbstractArtificial neural networks ANNs are flexible computing tools that have been applied to a wide range of domains with a notable level of accuracy. However, there are multiple choices of ANNs classifiers in the literature that produce dissimilar results. As a consequence of this, the selection of this classifier is crucial for the overall performance of the system. In this work, an integral framework is proposed for the optimization of different ANN classifiers based on statistical hypothesis testing. The framework is tested in a real ballistic scenario. The new quality measures introduced, based on the Student t-test, and employed throughout the framework, ensure the validity of results from a statistical standpoint; they reduce the appearance of experimental errors or the appearance of possible randomness. Results show the relevance of this framework, proving that its application improves the performance and efficiency of multiple classifiers. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1111/j.1468-0394.2012.00653.x | Periodicals |
Keywords | Field | DocType |
artificial intelligence,artificial neural networks | Data mining,Computer science,Network topology,Artificial intelligence,Classifier (linguistics),Artificial neural network,Statistical hypothesis testing,Machine learning,Randomness | Journal |
Volume | Issue | ISSN |
31 | 1 | 0266-4720 |
Citations | PageRank | References |
2 | 0.36 | 34 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Israel Gonzalez-Carrasco | 1 | 70 | 7.19 |
| Ángel García-crespo | 2 | 553 | 38.57 |
| Belén Ruíz-mezcua | 3 | 66 | 9.88 |
| José Luis López Cuadrado | 4 | 24 | 4.20 |
| Ricardo Colomo-Palacios | 5 | 614 | 67.78 |