minisom
:red_circle: MiniSom is a minimalistic implementation of the Self Organizing Maps (by JustGlowing)
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. (by rymc)
| minisom | n2d | |
|---|---|---|
| 3 | 1 | |
| 1,388 | 122 | |
| - | - | |
| 8.4 | 0.0 | |
| 3 days ago | 6 months ago | |
| Python | Python | |
| 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.
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.
- How to use MiniSOM (Self Organizing Maps) Library
- [P][D] Self Organizing Maps
-
[OC] Animation of a Self Organizing Map
I made this animation because I could not find a single decent demonstration of a SOM map on the internet, especially considering how popular it is becoming. I used the python library Pyvista for 3D plotting and creating the animation, and I used the minisom library for running the SOM.
n2d
Posts with mentions or reviews of n2d.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-09-12.
-
Time-Series image clustering. Advice needed!
So far I found some approaches that looks promising, for example n2d or k-means with DTW distance, and there are some more (e.g. T-DPSOM), but I want to start from these.
What are some alternatives?
When comparing minisom and n2d you can also consider the following projects:
umap - Uniform Manifold Approximation and Projection
somoclu - Massively parallel self-organizing maps: accelerate training on multicore CPUs, GPUs, and clusters
sparse-som - Efficient Self-Organizing Map for Sparse Data
susi - SuSi: Python package for unsupervised, supervised and semi-supervised self-organizing maps (SOM)
DBCV - Python implementation of Density-Based Clustering Validation
som-tsp - Solving the Traveling Salesman Problem using Self-Organizing Maps
awesome-community-detection - A curated list of community detection research papers with implementations.