Distances and Similarities in Data Analysis

Michel Marie Deza and Elena Deza
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Michel Marie Deza: École Normale Supérieure
Elena Deza: Moscow State Pedagogical University

Chapter Chapter 17 in Encyclopedia of Distances, 2013, pp 291-305 from Springer

Abstract: Abstract A data set is a finite set comprising m sequences $(x^{j}_{1},\ldots, x^{j}_{n})$ , j∈{1,…,m}, of length n. The values $x^{1}_{i},\ldots, x^{m}_{i}$ represent an attribute S i . It can be numerical, including continuous (real numbers) and binary (presence/absence expressed by 1/0), ordinal (numbers expressing rank only), or nominal (which are not ordered).

Keywords: Mahalanobis Distance; Cosine Similarity; Curtis Similarity; Binary Case; Tanimoto Similarity (search for similar items in EconPapers)
Date: 2013
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DOI: 10.1007/978-3-642-30958-8_17

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