SOMPY
A Python library implementing Self-Organizing Maps (SOM) with batch training, PCA initialization, and visualization tools.
What is SOMPY?
SOMPY is a Python library for implementing Self-Organizing Maps (SOM), an unsupervised neural network technique used for dimensionality reduction, clustering, and data visualization. It provides tools for training SOMs with batch processing, initializing maps using PCA, and visualizing results through component planes and U-Matrices.
Data scientists, researchers, and machine learning practitioners working with unsupervised learning, dimensionality reduction, or exploratory data analysis who prefer a Python-based alternative to Matlab's somtoolbox.
SOMPY offers a carefully optimized, Pythonic implementation of SOM with integration to popular scientific libraries (scikit-learn, scipy), making it accessible for prototyping and analysis while maintaining performance through matrix calculation optimizations.
Overview
A Python Library for Self Organizing Map (SOM)
Use Cases
Best For
- Reducing high-dimensional data for visualization and clustering
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