University of Hertfordshire Research Archive

        JavaScript is disabled for your browser. Some features of this site may not work without it.

        Browse

        All of UHRABy Issue DateAuthorsTitlesThis CollectionBy Issue DateAuthorsTitles

        Arkivum Files

        My Downloads
        View Item 
        • UHRA Home
        • University of Hertfordshire
        • Research publications
        • View Item
        • UHRA Home
        • University of Hertfordshire
        • Research publications
        • View Item

        The Architecture and Performance of a Stochastic Competitive Evolutionary Neural Tree Network

        View/Open
        Final Accepted Version (PDF, 167Kb)
        Author
        Davey, N.
        Adams, R.G.
        George, S.
        Attention
        2299/601
        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.
        Publication date
        2000
        Published in
        Applied Intelligence
        Published version
        https://doi.org/10.1023/A:1008364004705
        Other links
        http://hdl.handle.net/2299/601
        Relations
        School of Computer Science
        Metadata
        Show full item record
        Keep in touch

        © 2018 University of Hertfordshire

        I want to...

        • Apply for a course
        • Download a Prospectus
        • Find a job at the University
        • Make a complaint
        • Contact the Press Office

        Go to...

        • Accommodation booking
        • Your student record
        • Bayfordbury
        • KASPAR
        • UH Arts

        The small print

        • Terms of use
        • Privacy and cookies
        • Criminal Finances Act 2017
        • Modern Slavery Act 2015
        • Sitemap

        Find/Contact us

        • T: +44 (0)1707 284000
        • E: ask@herts.ac.uk
        • Where to find us
        • Parking
        • hr
        • qaa
        • stonewall
        • AMBA
        • ECU Race Charter
        • disability confident
        • AthenaSwan