Three Similarity Measures between One-Dimensional Data Sets
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| Natura: | Artículo científico |
| Lingua: | en |
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Universidad Nacional de Colombia
2014
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| _version_ | 1876462275053748224 |
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| author | Luis Gonzalez-Abril |
| author_facet | Luis Gonzalez-Abril |
| contents | Three Similarity Measures between One-Dimensional Data Sets Luis Gonzalez-Abril Jose M. Gavilan Francisco Velasco Morente Física, Astronomía y Matemáticas Non Data mining Kernel methods parametric tests Interval distance 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. 2014 artículo científico 0120-1751 https://www.redalyc.org/articulo.oa?id=89931327006 en http://www.redalyc.org/revista.oa?id=899 Revista Colombiana de Estadística application/pdf Universidad Nacional de Colombia Revista Colombiana de Estadística (Colombia) Num.1 Vol.37 |
| format | Artículo científico |
| id | redalyc_89931327006 |
| institution | Redalyc |
| language | en |
| publishDate | 2014 |
| publisher | Universidad Nacional de Colombia |
| spellingShingle | Three Similarity Measures between One-Dimensional Data Sets Luis Gonzalez-Abril Física, Astronomía y Matemáticas Non Data mining Kernel methods parametric tests Interval distance Three Similarity Measures between One-Dimensional Data Sets Luis Gonzalez-Abril Jose M. Gavilan Francisco Velasco Morente Física, Astronomía y Matemáticas Non Data mining Kernel methods parametric tests Interval distance 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. 2014 artículo científico 0120-1751 https://www.redalyc.org/articulo.oa?id=89931327006 en http://www.redalyc.org/revista.oa?id=899 Revista Colombiana de Estadística application/pdf Universidad Nacional de Colombia Revista Colombiana de Estadística (Colombia) Num.1 Vol.37 |
| title | Three Similarity Measures between One-Dimensional Data Sets |
| topic | Física, Astronomía y Matemáticas Non Data mining Kernel methods parametric tests Interval distance |
| url | https://www.redalyc.org/articulo.oa?id=89931327006 |