minisom VS sparse-som

Compare minisom vs sparse-som and see what are their differences.

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minisom sparse-som
3 1
1,387 18
- -
8.4 0.0
5 days ago over 3 years ago
Python C++
MIT License GNU General Public License v3.0 only
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

minisom

Posts with mentions or reviews of minisom. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-07-15.

sparse-som

Posts with mentions or reviews of sparse-som. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-07-15.

What are some alternatives?

When comparing minisom and sparse-som you can also consider the following projects:

umap - Uniform Manifold Approximation and Projection

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

somoclu - Massively parallel self-organizing maps: accelerate training on multicore CPUs, GPUs, and clusters

LeetCode-Solutions - 🏋️ Python / Modern C++ Solutions of All 3123 LeetCode Problems (Weekly Update)

DBCV - Python implementation of Density-Based Clustering Validation

Kratos - Kratos Multiphysics (A.K.A Kratos) is a framework for building parallel multi-disciplinary simulation software. Modularity, extensibility and HPC are the main objectives. Kratos has BSD license and is written in C++ with extensive Python interface.

som-tsp - Solving the Traveling Salesman Problem using Self-Organizing Maps

n2d - A deep clustering algorithm. Code to reproduce results for our paper N2D: (Not Too) Deep Clustering via Clustering the Local Manifold of an Autoencoded Embedding.

awesome-community-detection - A curated list of community detection research papers with implementations.