n2d VS minisom

Compare n2d vs minisom and see what are their differences.

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)
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n2d minisom
1 3
122 1,387
- -
0.0 8.4
6 months ago 5 days ago
Python Python
GNU General Public License v3.0 only MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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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!
    2 projects | /r/gis | 12 Sep 2021
    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.

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.

What are some alternatives?

When comparing n2d and minisom 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.