University of Hertfordshire

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  • 900009.pdf

    Accepted author manuscript, 168 KB, PDF document

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Original languageEnglish
Pages (from-to)75-93
JournalApplied Intelligence
Volume12
Issue1/2
DOIs
Publication statusPublished - 2000

Abstract

A new dynamic tree structured network - the Stochastic Competitive Evolutionary Neural Tree (SCENT) is introduced. The network is able to provide a hierarchical classification of unlabelled data sets. The main advantage that SCENT offers over other hierarchical competitive networks is its ability to self-determine the number and structure of the competitive nodes in the network without the need for externally set parameters. The network produces stable classificatory structures by halting its growth using locally calculated, stochastically controlled, heuristics. The performance of the network is analysed by comparing its results with that of a good non-hierarchical clusterer, and with three other hierarchical clusterers and its non stochastic predecessor. SCENT’s classificatory capabilities are demonstrated by its ability to produce a representative hierarchical structure to classify a broad range of data sets.

Notes

The original publication is available at www.springerlink.com . Copyright Springer. DOI : 10.1023/A:1008364004705

ID: 92348