Welcome to som-pbc’s documentation!
som-pbc
Authors: Alex Müller
Copyright: (c) 2017 - 2022; Alex Müller
This package contains a simple self-organizing map implementation in Python with periodic boundary conditions.
Self-organizing maps are also called Kohonen maps and were invented by Teuvo Kohonen.[1] They are an unsupervised machine learning technique to efficiently create spatially organized internal representations of various types of data. For example, SOMs are well-suited for the visualization of high-dimensional data.
This is a simple implementation of SOMs in Python. This SOM has periodic
boundary conditions and therefore can be imagined as a “donut”. The
implementation uses numpy
, scipy
, scikit-learn
and
matplotlib
.
The project’s GitHub page can be found here: http://github.com/alexarnimueller/som