Metrics in symbolic data analysis

0Citations
Citations of this article
12Readers
Mendeley users who have this article in their library.
Get full text

Abstract

The Authors consider the general problem of similarity and dissimilarity measures in Symbolic Data Analysis. First they examine the classical definitions of elementary event, assertion object, hierarchical dependences and logical dependences, then they consider some well-known measures resemblance measures between two objects (Sokal-Michener, Roger-Tanimoto, Sokal-Sneath, Dice-Czekanowski-Sorenson, Russel-Rao). For resemblance measures based on aggregation functions, the authors consider the proposals of Gowda-Diday, De Baets et al., Malerba et al., Vladutu et al, and Ichino-Yaguchi.

Cite

CITATION STYLE

APA

Nieddu, L., & Rizzi, A. (2005). Metrics in symbolic data analysis. In Studies in Classification, Data Analysis, and Knowledge Organization (Vol. 0, pp. 71–78). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/3-540-27373-5_9

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free