Statistical Selection of Relevant Features to Classify Random, Scale Free and Exponential Networks (original) (raw)

Innovations in Hybrid Intelligent Systems, 2007

Abstract

In this paper a statistical selection of relevant features is presented. An experiment was designed to select relevant and not redundant features or characterization functions, which allow quantitatively discriminating among different types of complex networks. As well there exist researchers given to the task of classifying some networks of the real world through characterization functions inside a type of complex network, they do not give enough evidences of detailed analysis of the functions that allow to determine if all are necessary ...

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