Three Similarity Measures between One-Dimensional Data Sets

Based on an interval distance, three functions are given in order to quantify similarities between one-dimensional data sets by using rst-order statistics. The Glass Identication Database is used to illustrate how to analyse a data set prior to its classication and/or to exclude dimensions. Furtherm...

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Bibliographic Details
Published inRevista Colombiana de estadística Vol. 37; no. 1; p. 79
Main Authors Gavilan, Jose M., Morente, Francisco Velasco
Format Journal Article
LanguageEnglish
Published Bogota Universidad Nacional de Colombia 09.07.2014
Subjects
Data mining
Statistical analysis
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Summary:Based on an interval distance, three functions are given in order to quantify similarities between one-dimensional data sets by using rst-order statistics. The Glass Identication Database is used to illustrate how to analyse a data set prior to its classication 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.
ISSN:0120-1751
2389-8976
DOI:10.15446/rce.v37n1.44359