Papavasileiou, E., & Jansen, B. (2017). The Importance of Topology Initialization in FS-NEAT and FD-NEAT. Poster session presented at NSE PhD Day 2017, Brussels, Belgium.

@conference{d5591e1062234068aa2d065ea9635c51,
title = "The Importance of Topology Initialization in FS-NEAT and FD-NEAT",
abstract = "Feature Selective Neuroevolution of Augmenting Topologies (FS-NEAT) and Feature Deselective Neuroevolution of Augmenting Topologies (FD-NEAT) are two popular methods for optimizing the topology and the weights of Artificial Neural Networks (ANNs) while simultaneously performing feature selection. However, no study exists that investigates the effects of changing the networks' initial topologies. In this study we investigate how the introduction of a hidden layer and a different connectivity setting in the initial topologies can affect the performance of the algorithms in terms of accuracy, efficiency and ability of performing feature selection. For this purpose we employ artificial datasets of increasing complexity based on the exclusive-or (XOR) problem with irrelevant features. The results show that the introduction of a hidden layer can affect the performance of the two algorithms, resulting in higher accuracy, faster convergence and better feature selection abilities whereas the initial connectivity setting does not affect their performance.",
author = "Evgenia Papavasileiou and Bart Jansen",
year = "2017",
language = "English",
note = "NSE PhD Day 2017 ; Conference date: 08-06-2017",
}