Distances and Other Dissimilarity Measures in Chemometrics

Several similarity/diversity measures for data mining and chemometrics are presented and discussed toward the different data they are applied to. After a short presentation of the axioms for dissimilarity and similarity functions, their relationships, and the required data pretreatment, the theoretical definitions and formulas of distance and similarity measures for real‐valued, binary, ranked, frequency, and mixed‐type data are provided along with the main concepts on distances between sets and meta‐distances. Simple examples of calculation are given, and extended comparisons are performed on the distances defined for real‐valued and binary data.