Dependence maps, a dimensionality reduction with dependence distance for high-dimensional data

• Autores: Kichun Lee, Alexander Gray, Heeyoung Kim
• Localización: Data mining and knowledge discovery, ISSN 1384-5810, Vol. 26, Nº 3, 2013, págs. 512-532
• Idioma: inglés
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• Resumen

  • We introduce the dependence distance, a new notion of the intrinsic distance between points, derived as a pointwise extension of statistical dependence measures between variables. We then introduce a dimension reduction procedure for preserving this distance, which we call the dependence map. We explore its theoretical justification, connection to other methods, and empirical behavior on real data sets.We introduce the dependence distance, a new notion of the intrinsic distance between points, derived as a pointwise extension of statistical dependence measures between variables. We then introduce a dimension reduction procedure for preserving this distance, which we call the dependence map. We explore its theoretical justification, connection to other methods, and empirical behavior on real data sets.