#Kohonen Self Organizing Maps (SOM) - python algorithms
This project contains a python implementation of several algorithms related to the self organizing maps of kohonen. For more information on Kohonen maps refer to (http://en.wikipedia.org/wiki/Self-organizing_map).
base/
contains base python code for manipulating datasets, defining the algorithms common interface and other machine learning tools and helpers (like cross validation, distance calculations, etc).
algorithms/
contains all algorithms implementation:
- kohonen: kohonen som maps algorithm implementation
variants:
- recsom: recursive self organizing maps variant implementation
other algorithms:
- knn: k-nearest neighbors algorithm implementation
- kmeans: k-means algorithm implementation
- stochastickmeans: stochastic k-means variant of k-means algorithm implementaion
- lvq: linear vector quantization algorithm implementation
- svm: support vector machines algorithm interface
datasets/
contains sample dataset to play with the algorithms and compare their results.
Note: In order to get all python scripts to work, the root directory (kohonen/) must be in the PYTHONPATH.