2010 Annual Meeting of the North American Fuzzy Information Processing Society 2010
DOI: 10.1109/nafips.2010.5548299 View full text |Buy / Rent full text
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“…These low-dimensional representations of the original data can be used for different follow-up tasks, such as visualization, clustering, classification and so on. Dimensionality reduction has been studied for several decades [4][5][6]. By exploring and exploiting the geometric structure of samples from different perspectives, various unsupervised dimensionality reduction methods have been proposed [7].…”
Section: Introductionmentioning
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“…These low-dimensional representations of the original data can be used for different follow-up tasks, such as visualization, clustering, classification and so on. Dimensionality reduction has been studied for several decades [4][5][6]. By exploring and exploiting the geometric structure of samples from different perspectives, various unsupervised dimensionality reduction methods have been proposed [7].…”
Section: Introductionmentioning