[2] It is considered a non-linear approach as the mapping cannot be represented as a linear combination of the original variables as possible in techniques such as principal component analysis, which also makes it more difficult to use for classification applications.
[3] Denote the distance between ith and jth objects in the original space by
The number of iterations needs to be experimentally determined and convergent solutions are not always guaranteed.
Many implementations prefer to use the first Principal Components as a starting configuration.
[4] The Sammon mapping has been one of the most successful nonlinear metric multidimensional scaling methods since its advent in 1969, but effort has been focused on algorithm improvement rather than on the form of the stress function.