Title :
An Empirical Study of the Influence of Data Structures on the Performance of VG-RAM Classifiers
Author :
Alves, Daniel S. F. ; Cardoso, Douglas O. ; Carneiro, Hugo C. C. ; Franca, Felipe M. G. ; Lima, Priscila M. V.
Author_Institution :
PESC - COPPE, Univ. Fed. do Rio de Janeiro, Rio de Janeiro, Brazil
Abstract :
This work investigates the effect of different data structures on the performance and accuracy of VG-RAM-based classifiers. This weightless neural model is based on RAM nodes having very large address input, what suggests the use of special data structures in order to deal with space and time computational costs. Four different data structures are explored, including the classical one used in recent VG-RAM related literature, resulting in a novel and accurate yet fast setup.
Keywords :
data structures; neural nets; pattern classification; random-access storage; RAM nodes; VG-RAM classifier performance; data structures; space computational costs; time computational costs; virtual generalizing random access memory; weightless neural model; Accuracy; Biological neural networks; Data structures; Neurons; Random access memory; Time complexity; Training; VG-RAM; data structures; weightless neural networks;
Conference_Titel :
Computational Intelligence and 11th Brazilian Congress on Computational Intelligence (BRICS-CCI & CBIC), 2013 BRICS Congress on
Conference_Location :
Ipojuca
DOI :
10.1109/BRICS-CCI-CBIC.2013.71
