GDL

Journal from gdlhub / 2017-08-14 13:34:20
By : Souad Larabi Marie-Sainte, King Saud University
Created : 2017-01-14, with 1 files

Keyword : Exploratory Projection Pursuit; Genetic Algorithm; Particle Swarm Optimiza- tion; Tribes; Clustering; Outliers
Url : http://www.sciencedirect.com/science/article/pii/S1319157816300234
Document Source : web

This article consists of using biologically inspired algorithms in order to detect


potentially interesting structures in large and multidimensional data sets. Data exploration and


the detection of interesting structures are based on the use of Projection Pursuit that involves the


definition and the optimization of an index associated with each direction or projection. The opti-


mization of a projection index should provide a set of multiple optima that is expected to corre-


spond to interesting graphical representations in low dimensional space. The implementation of


the bio-inspired algorithms along with the projection pursuit develops a new software called


EPP-Lab. Projection pursuit is widely used in different scientific domains (biology, pharmacy,


bioinformatics, biometry, etc) but not widely present in the well-known softwares. EPP-Lab is ded-


icated to recognize and visualize clusters and outlying observations on one dimension from high


dimensional and multivariate data sets. It includes different statistical techniques for results analy-


sis. It provides several features and gives the user the option to adjust the parameters of the selected


bio-inspired methods or to use defaults values. EPP-Lab is a unique software for detection, visual-


ization and analysis of non-linear structures. The performance of this tool has been validated by


testing different real and simulated data sets.

Ó


2016 The Author. Production and hosting by Elsevier B.V. on behalf of King Saud University. This is an


open access article under the CC BY-NC-ND license (


http://creativecommons.org/licenses/by-nc-nd/4.0/


)

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