%0 Generic
%A Touwen, Lourens
%A Bucur, Doina
%A van der Hofstad, Remco
%A Litvak, Nelly
%D 2023
%T Data underlying the publication: Learning the mechanisms of network growth
%U 
%R 10.4121/0b40e329-7b33-4b8f-a289-ab6d1893b437.v1
%K synthetic networks
%K preferential attachment
%K networks with fitness
%K networks with aging
%K uniform attachment
%K machine learning
%K model selection for complex networks
%K complex networks
%X <p>This dataset accompanies the paper `Learning the mechanisms of network growth' by the same authors. The dataset contains 6733 networks of size 20,000 each generated in accordance to different combination of three mechanisms: fitness, aging and preferential attachment. The goal is to use machine learning to identify the combination of mechanisms that was used to create the network. The dataset includes static features from the literature and two version of our newly developed dynamic features. <span style="color: rgba(0, 0, 0, 0);"> network growth</span></p>
%I 4TU.ResearchData