pekalska: Pekalska's approach to speeding up Sammon's mapping.
Description
Creates a k-dimensional representation of the data. As input, a subsample and
its k-dimensional mapping are required. The method approximates the subsample
mapping to a linear mapping based on the distances matrix of the subsample
and then applies the same mapping to all instances.
Usage
pekalska(D, sample.indices = NULL, Ys = NULL)
Arguments
D
dist object or distances matrix.
sample.indices
The indices of subsamples.
Ys
The subsample mapping (k-dimensional).
Value
The low-dimensional representation of the data.
References
Pekalska, E., de Ridder, D., Duin, R. P., & Kraaijveld, M. A.
(1999). A new method of generalizing Sammon mapping with application to
algorithm speed-up (pp. 221-228).