multidimensional scaling

n. (MDS) A scaling procedure in which similarities in a data set are represented by spatial proximity, and differences are represented by distal spacing in an artificial space of any number of dimensions. MDS is often used as an alternative to factor analysis as it can use computations other than linear correlations to represent spatial dimensions.