Continuous Iterative Guided Spectral Class Rejection Classification Algorithm: Part 1

dc.contributor.authorPhillips, Rhonda D.en
dc.contributor.authorWatson, Layne T.en
dc.contributor.authorWynne, Randolph H.en
dc.contributor.authorRamakrishnan, Narenen
dc.contributor.departmentComputer Scienceen
dc.date.accessioned2013-06-19T14:36:47Zen
dc.date.available2013-06-19T14:36:47Zen
dc.date.issued2009en
dc.description.abstractThis paper outlines the changes necessary to convert the iterative guided spectral class rejection (IGSCR) classification algorithm to a soft classification algorithm. IGSCR uses a hypothesis test to select clusters to use in classification and iteratively refines clusters not yet selected for classification. Both steps assume that cluster and class memberships are crisp (either zero or one). In order to make soft cluster and class assignments (between zero and one), a new hypothesis test and iterative refinement technique are introduced that are suitable for soft clusters. The new hypothesis test, called the (class) association significance test, is based on the normal distribution, and a proof is supplied to show that the assumption of normality is reasonable. Soft clusters are iteratively refined by creating new clusters using information contained in a targeted soft cluster. Soft cluster evaluation and refinement can then be combined to form a soft classification algorithm, continuous iterative guided spectral class rejection (CIGSCR).en
dc.format.mimetypeapplication/pdfen
dc.identifierhttp://eprints.cs.vt.edu/archive/00001070/en
dc.identifier.sourceurlhttp://eprints.cs.vt.edu/archive/00001070/01/cigscr1.pdfen
dc.identifier.trnumberTR-09-09en
dc.identifier.urihttp://hdl.handle.net/10919/20284en
dc.language.isoenen
dc.publisherDepartment of Computer Science, Virginia Polytechnic Institute & State Universityen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectAlgorithmsen
dc.subjectData structuresen
dc.titleContinuous Iterative Guided Spectral Class Rejection Classification Algorithm: Part 1en
dc.typeTechnical reporten
dc.type.dcmitypeTexten

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