Abstract
The paper presents an introduction to automated methods of classification and assignment, with particular reference to their use in the analysis of soil data. Material covered includes: types of variable describing a soil sample; measures of dissimilarity; clustering criteria and algorithms; representation of data as points in a low‐dimensional space; assessment of classifications; incorporation into a classification of spatial relationships between soil samples; assignment of objects to the population with maximum posterior probability; assignment procedures for data described by variables of mixed type; kernel density estimation; assignment to spatially‐located populations.