SimpSOM is a lightweight implementation of Kohonen Self-Organizing Maps (SOM) for Python 3, useful for unsupervised learning, clustering and dimensionality reduction.
To install this package, clone this repository and install it with
python setup.py install
. Alternatively you can download it from PyPI,
to retrieve it just type pip install simpsom
, but make sure the
version you need is available on the database.
It allows you to build and train SOM on your dataset, save/load the trained
network weights, and display or print graphs of the network with
selected features. The function run_colors_example()
will run a toy
model, where a number of colors will be mapped from the 3D RGB space to
the 2D network map and clustered according to their similarity in the
origin space.
- Class and function names have been updated to adhere to PEP8.
- Batch training has been added and is now the default algorithm.
- A light parallelization is now possible with RAPIDS.
This version introduces a number of changes, while attempting to maintain the original philosophy of this project: a SOM library easy to understand and customize. Functions and classes names have been changed to improve readability. If you are migrating from an older version (<=1.3.4), please make sure to check the API first!