Methods of Collective Intelligence in Exploratory Data Analysis: A Research Survey

Abstract

This study contains a brief presentation of the basic tasks for Exploratory Data Analysis (EDA), namely: classification, clustering, reduction of data dimensionality and number of data instances as well as detection of outliers. Herein, solutions to the aforementioned problems incorporating a wide range of computational intelligence algorithms, in particular procedures based on collective intelligence, are under consideration. Furthermore, the combination of metaheuristic algorithms with basic EDA procedures applied and verified within many domains of science, technology and engineering are being presented.

On the Use of Nature Inspired Metaheuristic in Computer Game

“…Furthermore, it has been applied in medical tasks [29], for data base domains [30], in mechanism and machine theory [31], in clustering tasks [32], [33], and also in neural learning processes [34]. Extensive use of this algorithm has been collected in the article [35].…”