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Kohonen Self Organizing Maps algorithm implementation in python, with other machine learning algorithms for comparison (kmeans, knn, svm, etc)

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#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.

kohonen

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