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Jose M. Gavilan ; Francisco Velasco Morente ;Revista Colombiana de Estadística 2014, 37 1

Autor: Luis Gonzalez-Abril



Revista Colombiana de Estadística ISSN: 0120-1751 Universidad Nacional de Colombia Colombia Gonzalez-Abril, Luis; Gavilan, Jose M.; Velasco Morente, Francisco Three Similarity Measures between One-Dimensional Data Sets Revista Colombiana de Estadística, vol.
37, núm.
1, junio, 2014, pp.
79-94 Universidad Nacional de Colombia Bogotá, Colombia Available in: How to cite Complete issue More information about this article Journals homepage in Scientific Information System Network of Scientific Journals from Latin America, the Caribbean, Spain and Portugal Non-profit academic project, developed under the open access initiative Revista Colombiana de Estadística Junio 2014, volumen 37, no.
1, pp.
79 a 94 Three Similarity Measures between One-Dimensional Data Sets Tres medidas de similitud entre conjuntos de datos unidimensionales Luis Gonzalez-Abril1,a , Jose M.
Gavilan1,b , Francisco Velasco Morente1,c 1 Departamento de Economía Aplicada I, Facultad de Ciencias Económicas y Empresariales, Universidad de Sevilla, Sevilla, Spain Abstract Based on an interval distance, three functions are given in order to quantify similarities between one-dimensional data sets by using first-order statistics.
The Glass Identification Database is used to illustrate how to analyse a data set prior to its classification and-or to exclude dimensions.
Furthermore, a non-parametric hypothesis test is designed to show how these similarity measures, based on random samples from two populations, can be used to decide whether these populations are identical.
Two comparative analyses are also carried out with a parametric test and a non-parametric test.
This new non-parametric test performs reasonably well in comparison with classic tests. Key words: Data mining, Interval distance, Kernel methods, Non-parametric tests. Resumen Basadas en una distancia intervalar, se dan tres funciones para cuantifi...

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