Self Organizing Maps Package
Project description
lightSOM
A Python Library for Self Organizing Map (SOM)
As much as possible, the structure of SOM is similar to somtoolbox
in Matlab. It has the following functionalities:
- Only Batch training, which is faster than online training. It has parallel processing option similar to
sklearn
format and it speeds up the training procedure, but it depends on the data size and mainly the size of the SOM grid.I couldn't manage the memory problem and therefore, I recommend single core processing at the moment. But nevertheless, the implementation of the algorithm is carefully done for all those important matrix calculations, such asscipy
sparse matrix andnumexpr
for calculation of Euclidean distance. - PCA (or RandomPCA (default)) initialization, using
sklearn
or random initialization. - component plane visualization (different modes).
- Hitmap.
- U-Matrix visualization.
- 1-d or 2-d SOM with only rectangular, planar grid. (works well in comparison with hexagonal shape, when I was checking in Matlab with somtoolbox).
- Different methods for function approximation and predictions (mostly using Sklearn).
Dependencies:
SOMPY has the following dependencies:
- numpy
- scipy
- scikit-learn
- numexpr
- matplotlib
- pandas
- ipdb
Installation:
pip install lightSOM
For more information, you can contact me via sevamoo@gmail.com or svm@arch.ethz.ch, but please report an issue first.
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