Some Distance Measures and Their Use in Feature Selection

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dc.citation.bibtexNametechreporten_US
dc.citation.issueNumber7611en_US
dc.citation.journalTitleRice University ECE Technical Reporten_US
dc.citation.volumeNumberTR7611en_US
dc.contributor.authorPapantoni-Kazakos, P.en_US
dc.date.accessioned2007-10-31T00:57:54Z
dc.date.available2007-10-31T00:57:54Z
dc.date.issued1976-11-20
dc.date.modified2003-10-22en_US
dc.date.submitted2003-07-20en_US
dc.descriptionTech Reporten_US
dc.description.abstractThe Bhattacharyya, I-divergence, Vasershtein, variational and Levy distances are evaluated, compared and used for the reduction of n data to one feature. This reduction is obtained through a restricted linear transformation and the original data are assumed to be originating from two different jointly Gaussian classes. It is found that the Bhattacharyya, I-divergence and Vasershtein distances give the same "optimal" linear transformation that applied on the original n data result in one feature with maximum possible distance between classes. The distortion measures considered in the Vasershtein distance are |x-y| and (x-y)<sup>2</sup>. For the same distance measures and classes with equal covariances the Levy distance results in the same "optimal" linear transformation.en_US
dc.description.sponsorshipAir Force Office of Scientific Researchen_US
dc.identifier.citationP. Papantoni-Kazakos, "Some Distance Measures and Their Use in Feature Selection," <i>Rice University ECE Technical Report,</i> vol. TR7611, no. 7611, 1976.
dc.identifier.urihttps://hdl.handle.net/1911/20197
dc.language.isoeng
dc.subjectmeasures*
dc.subjectdistance*
dc.subject.keywordmeasuresen_US
dc.subject.keyworddistanceen_US
dc.titleSome Distance Measures and Their Use in Feature Selectionen_US
dc.typeReport
dc.type.dcmiText
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