id: 01630219
dt: j
an: 01630219
au: Vesanto, Juha
ti: SOM-based data visualization methods.
so: Intell. Data Anal. 3, No.2, 111-126 (1999).
py: 1999
pu: IOS Press, Amsterdam
la: EN
cc: 
ut: self-organizing map; data mining; visualization; vector quantization;
    projection
ci: 
li: doi:10.1016/S1088-467X(99)00013-X
ab: Summary: The self-organizing map (SOM) is an efficient tool for
    visualization of multidimensional numerical data. In this paper, an
    overview and categorization of both old and new methods for the
    visualization of SOM is presented. The purpose is to give an idea of
    what kind of information can be acquired from different presentations
    and how the SOM can best be utilized in exploratory data visualization.
    Most of the presented methods can also be applied in the more general
    case of first making a vector quantization (e.g. $k$-means) and then a
    vector projection (e.g. Sammon’s mapping).
rv: