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Training Set Size for Generalization Ability of Artificial Neural Networks in Forecasting TCP/IP Traffic Trends
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 113 - Number 13 |
| Year of Publication: 2015 |
| Authors: Vusumuzi Moyo, Khulumani Sibanda |
10.5120/19885-1902
|
Vusumuzi Moyo, Khulumani Sibanda . Training Set Size for Generalization Ability of Artificial Neural Networks in Forecasting TCP/IP Traffic Trends. International Journal of Computer Applications. 113, 13 ( March 2015), 14-19. DOI=10.5120/19885-1902
Abstract
In this paper we empirically investigate various sizes of training sets with the aim of determining the optimum training set size for generalization ability of an ANN trained on forecasting TCP/IP network traffic trends. We found from both the simulation experiments and literature that the best training set size can be obtained by selecting training samples randomly, between the interval 5×N_W and 10×N_W in number, depending on the difficulty of the problem under consideration.
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