On comparing two sequences of numbers and its applications to clustering analysis

Campello, R.J.G.B., and Hruschka, E. (2009) On comparing two sequences of numbers and its applications to clustering analysis. Information Sciences, 179 (8). pp. 1025-1039.

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A conceptual problem that appears in different contexts of clustering analysis is that of measuring the degree of compatibility between two sequences of numbers. This problem is usually addressed by means of numerical indexes referred to as sequence correlation indexes. This paper elaborates on why some specific sequence correlation indexes may not be good choices depending on the application scenario in hand. A variant of the Product-Moment correlation coefficient and a weighted formulation for the Goodman-Kruskal and Kendall's indexes are derived that may be more appropriate for some particular application scenarios. The proposed and existing indexes are analyzed from different perspectives, such as their sensitivity to the ranks and magnitudes of the sequences under evaluation, among other relevant aspects of the problem. The results help suggesting scenarios within the context of clustering analysis that are possibly more appropriate for the application of each index.

Item ID: 47618
Item Type: Article (Research - C1)
ISSN: 1872-6291
Keywords: clustering analysis, Goodman-Kruskal index, Kendall's index, Pearson Product-Moment index, Spearman's index, sensitivity analysis
Funders: CNPq, Brazil, FAPESP Brazil
Date Deposited: 08 Mar 2017 07:40
FoR Codes: 01 MATHEMATICAL SCIENCES > 0104 Statistics > 010401 Applied Statistics @ 100%
SEO Codes: 97 EXPANDING KNOWLEDGE > 970101 Expanding Knowledge in the Mathematical Sciences @ 100%
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