minisom and SOM-Kohonen-C-Engine
MiniSom is a practical Python library for accessibility and experimentation, while the C99 engine is a specialized high-performance backend for computationally intensive production clustering tasks—they could complement each other if the Python implementation needed to offload heavy lifting to compiled code, but are primarily competitors for different use cases.
About minisom
JustGlowing/minisom
:red_circle: MiniSom is a minimalistic implementation of the Self Organizing Maps
Built on NumPy with optional Numba JIT acceleration, it enables dimensionality reduction of high-dimensional data into low-dimensional grid visualizations while supporting both online and batch training modes. Features include configurable grid topologies (rectangular/hexagonal), winner neuron detection, model persistence via pickle, and applications spanning clustering, color quantization, and outlier detection. The vectorized NumPy-first design keeps dependencies minimal while maintaining extensibility for researchers and educators.
About SOM-Kohonen-C-Engine
MickaelDP/SOM-Kohonen-C-Engine
High-performance Self-Organizing Map (SOM) engine in C99. Unsupervised neural network for high-dimensional clustering (Fisher Iris & Palmer Penguins). Memory-safe implementation verified by Valgrind (0 leaks, 0 errors). Features tied-list BMU search, dynamic learning decay, and O3-optimized execution. Built from scratch.
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