uwot
An R package implementing the UMAP dimensionality reduction method. (by jlmelville)
umap
Uniform Manifold Approximation and Projection (by lmcinnes)
| uwot | umap | |
|---|---|---|
| 1 | 10 | |
| 307 | 6,959 | |
| - | - | |
| 8.5 | 8.3 | |
| 14 days ago | 4 days ago | |
| R | Python | |
| GNU General Public License v3.0 only | BSD 3-clause "New" or "Revised" License |
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.
uwot
Posts with mentions or reviews of uwot.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-10-11.
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UMAP clustering in Ruby
Umappp is a C++ library implemented by Aaron Lun. it is developed based on the R library uwot. it is implemented in C++ and uses OpenMP, so high performance is expected.
umap
Posts with mentions or reviews of umap.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-04-29.
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[OC] Clustering Images with OpenAI CLIP, T-SNE, UMAP & Plotly
UMAP GitHub repository: https://github.com/lmcinnes/umap
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UMAP clustering in Ruby
Uniform Manifold Approximation and Projection (UMAP) is a well-known dimensionality reduction method along with t-SNE.
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Introducing the Semantic Graph
A number of excellent topic modeling libraries exist in Python today. BERTopic and Top2Vec are two of the most popular. Both use sentence-transformers to encode data into vectors, UMAP for dimensionality reduction and HDBSCAN to cluster nodes.
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Using the 80:20 rule, what top 20% of your tools, statistical tests, activities, etc. do you use to generate 80% of your results?
As with anything, it depends on the problem. But T-SNE and UMAP are often good.
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[D] In UMAP and PyNNDescent, the conversion of Cosine and Correlation measures to distance metric seems problematic
UMAP distances.py: umap/distances.py at master · lmcinnes/umap (github.com)
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I built an Image Search Engine using OpenAI CLIP and Images from Wikimedia
I used for this project Flask and OpenAI CLIP. For the vector search I used approximate nearest neighbors provided by spotify/annoy. I used Flask-SQLAlchemy with GeoAlchemy2 to query GPS coordinates. The embedding was done using UMAP.
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We Analyzed 425,909 Favicons
side note: instead of t-SNE consider UMAP - provides better results (and it's much faster) https://github.com/lmcinnes/umap
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Finding correlating features in a large dataset.
Sounds like a job for UMAP https://github.com/lmcinnes/umap ?
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The most perplexing bug I've ever seen
I am a fairly experienced python developer/researcher (about 10 years), and have found a bug that breaks all of my intuitions. I am messing with the [UMAP](https://github.com/lmcinnes/umap) repository and trying to add the option to disable some additional features. I've stripped everything from it but have a [quick test that will run my UMAP version and compare the outputs with what the original gave](https://github.com/Andrew-Draganov/probabilistic_dim_reduction/blob/master/umap/nndescent_umap_test.py). Managing my random seeds, same inputs, all that.
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Question about numpy method I found in github project
I'm currently reading through a project on github, https://github.com/lmcinnes/umap, and in `umap/umap_.py` at line 2287, they have this:
What are some alternatives?
When comparing uwot and umap you can also consider the following projects:
numo-narray - Ruby/Numo::NArray - New NArray class library
minisom - :red_circle: MiniSom is a minimalistic implementation of the Self Organizing Maps
ruby-umappp - Uniform Manifold Approximation and Projection for Ruby
giotto-tda - A high-performance topological machine learning toolbox in Python
extpp - C++ Ruby extension API
annoy - Approximate Nearest Neighbors in C++/Python optimized for memory usage and loading/saving to disk
numo.hpp - C++ header for Numo and Rice
Traccar - Traccar GPS Tracking System
rice - Ruby Interface for C++ Extensions
vaex - Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python, ML, visualization and exploration of big tabular data at a billion rows per second 🚀
Rumale - Rumale is a machine learning library in Ruby
Openstreetmap - The Rails application that powers OpenStreetMap