self-organizing-map

Solving the Traveling Salesman Problem using Self-Organizing Maps

🔴 MiniSom is a minimalistic implementation of the Self Organizing Maps

Python library for Self-Organizing Maps

SuSi: Python package for unsupervised, supervised and semi-supervised self-organizing maps (SOM)

A GPU (CUDA) based Artificial Neural Network library

Explore high-dimensional datasets and how your algo handles specific regions.

🌐 Deep Embedded Self-Organizing Map: Joint Representation Learning and Self-Organization

Pytorch implementation of a Self-Organizing Map

A multi-gpu implementation of the self-organizing map in TensorFlow

Python implementation of the Epigenetic Robotic Architecture (ERA). It includes standalone classes for Self-Organizing Maps (SOM) and Hebbian Networks.

Hierarchical self-organizing maps for unsupervised pattern recognition

Machine Learning Library, written in J

Self-Organizing Map [https://en.wikipedia.org/wiki/Self-organizing_map] is a popular method to perform cluster analysis. SOM shows two main limitations: fixed map size constraints how the data is being mapped and hierarchical relationships are not easily recognizable. Thus Growing Hierarchical SOM has been designed to overcome this issues

Pytorch implementation of Self-Organizing Map(SOM). Use MNIST dataset as a demo.

Codes and Templates from the SuperDataScience Course

🌐 SOMperf: Self-organizing maps performance metrics and quality indices

Huge-scale, high-performance flow cytometry clustering in Julia

Rust library for Self Organising Maps (SOM).

FlowSOM algorithm in Python, using self-organizing maps and minimum spanning tree for visualization and interpretation of cytometry data