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

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

A GPU (CUDA) based Artificial Neural Network library

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

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

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

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

Pytorch implementation of a Self-Organizing Map

Hierarchical self-organizing maps for unsupervised pattern recognition

Machine Learning Library, written in J

Codes and Templates from the SuperDataScience Course

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

Rust library for Self Organising Maps (SOM).

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

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

Efficient Self-Organizing Map for Sparse Data

A photometric redshift monstrosity

Parallelized rotation and flipping INvariant Kohonen maps

Kohonen Self-Organizing Maps in Java

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

A PyTorch and Fastai based implementation of Self-Organizing Maps.

A demo of self-organizing maps using React, TypeScript and three.js

Autonomous Dynamic Learning Apprentice System

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

SOM clustering on IRIS dataset

It is Based on Anamoly Detection and by Using Deep Learning Model SOM which is an Unsupervised Learning Method to find patterns followed by the fraudsters.

Complete C implementation of the Kohonen Neural Network (SOM algorithm)

✨ Spark ML implementation of SOM algorithm (Kohonen self-organizing map)