h-plots for displaying nonmetric dissimilarity matrices
Metadatos
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Título
h-plots for displaying nonmetric dissimilarity matricesAutoría
Fecha de publicación
2013-01Editor
Wiley PeriodicalsISSN
1932-1864Cita bibliográfica
EPIFANIO, Irene. h‐plots for displaying nonmetric dissimilarity matrices. Statistical Analysis and Data Mining, 2013, 6.2: 136-143.Tipo de documento
info:eu-repo/semantics/articleVersión de la editorial
http://onlinelibrary.wiley.com/doi/10.1002/sam.11177/abstractVersión
info:eu-repo/semantics/sumittedVersionPalabras clave / Materias
Resumen
Nonmetric pairwise data with violations of symmetry, reflexivity, or triangle inequality appear in fields such as image matching, web mining, or cognitive psychology. When data are inherently nonmetric, we should not ... [+]
Nonmetric pairwise data with violations of symmetry, reflexivity, or triangle inequality appear in fields such as image matching, web mining, or cognitive psychology. When data are inherently nonmetric, we should not enforce metricity as real information could be lost. The multidimensional scaling problem is addressed from a new perspective. I propose a method based on the h-plot, which naturally handles asymmetric proximity data. Pairwise proximities between the objects are defined, though I do not embed these objects, but rather the variables that give the proximity to or from each object. The method is very simple to implement. The representation goodness can be easily assessed. The methodology is illustrated through several small examples and applied to the analysis of digital images of human corneal endothelia. Comparisons with well-known methods show its good behavior, especially with nonmetric pairwise data, which motivate my methodology. Other databases and methods are analyzed in the supporting information. [-]
Publicado en
Statistical Analysis and Data Mining (2013), Volume 6, Issue 2Derechos de acceso
© 2013 Wiley Periodicals, Inc. Statistical Analysis and Data Mining, 2013
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info:eu-repo/semantics/openAccess
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info:eu-repo/semantics/openAccess
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