Self-Organizing Maps, Principal Components and Non-negative ...

Self Organizing Maps
Principal Components, Curves and Surfaces
Non-negative Matrix Factorization
The simplest version of the SOM
Other version of the SOM
Example
Reconstruction Error
The method can be viewed as a version of K-means clustering.
The prototypes lie in a one- or two- dimensional manifold.
The resulting manifold is referred to as a constrained
topological map.
The original high dimensional observation can be mapped
down onto a two-dimensional coordinate system.
Karoline Geissler Self-Organizing Maps, Principal Components and Non-negative M