Some Distance Measures and Their Use in Feature Selection
dc.citation.bibtexName | techreport | en_US |
dc.citation.issueNumber | 7611 | en_US |
dc.citation.journalTitle | Rice University ECE Technical Report | en_US |
dc.citation.volumeNumber | TR7611 | en_US |
dc.contributor.author | Papantoni-Kazakos, P. | en_US |
dc.date.accessioned | 2007-10-31T00:57:54Z | en_US |
dc.date.available | 2007-10-31T00:57:54Z | en_US |
dc.date.issued | 1976-11-20 | en_US |
dc.date.modified | 2003-10-22 | en_US |
dc.date.submitted | 2003-07-20 | en_US |
dc.description | Tech Report | en_US |
dc.description.abstract | The 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.sponsorship | Air Force Office of Scientific Research | en_US |
dc.identifier.citation | P. Papantoni-Kazakos, "Some Distance Measures and Their Use in Feature Selection," <i>Rice University ECE Technical Report,</i> vol. TR7611, no. 7611, 1976. | en_US |
dc.identifier.uri | https://hdl.handle.net/1911/20197 | en_US |
dc.language.iso | eng | en_US |
dc.subject | measures | en_US |
dc.subject | distance | en_US |
dc.subject.keyword | measures | en_US |
dc.subject.keyword | distance | en_US |
dc.title | Some Distance Measures and Their Use in Feature Selection | en_US |
dc.type | Report | en_US |
dc.type.dcmi | Text | en_US |
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