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!