hdbscan VS 100DaysofMLCode

Compare hdbscan vs 100DaysofMLCode and see what are their differences.

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hdbscan 100DaysofMLCode
6 1
2,686 303
1.2% -
5.8 0.0
18 days ago 9 months ago
Jupyter Notebook Jupyter Notebook
BSD 3-clause "New" or "Revised" License MIT License
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Posts with mentions or reviews of hdbscan. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-09-16.
  • Introducing the Semantic Graph
    5 projects | dev.to | 16 Sep 2022
    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.
  • Hierarchical clustering algorithm
    1 project | /r/learnmachinelearning | 15 Apr 2022
  • Introduction to K-Means Clustering
    5 projects | news.ycombinator.com | 14 Mar 2022
    Working in spatial data science, I rarely find applications where k-means is the best tool. The problem is that it is difficult to know how many clusters you can expect on maps. Is it 5, 500, or 10,000? Here HDBSCAN [1] shines because it will cluster _and_ select the most suitable number of clusters, to cut the single linkage cluster tree.

    [1]: https://github.com/scikit-learn-contrib/hdbscan

  • New clustering algorithms like DBSCAN and OPTICS?
    1 project | /r/MLQuestions | 11 Jan 2022
    You might be interested in HDBSCAN which has several implementations, but the python implelementation is commonly used. That implementation makes use of algorithmic changes to significantly improve the computational complexity. Some more recent variations on that include the gamma-linkage variant which is quite powerful.
  • DBSCAN ALternatives?
    1 project | /r/MLQuestions | 26 Dec 2021
    The OPTICS algorithm is in the latest versions of sklearn and is a reasonable alternative to DBSCAN -- it has much the same theoretical foundation, but can cope with variable density clusters better. If you are willing to step outside sklearn itself there is also HDBSCAN which is a hierarchical clustering version of DBSCAN and is in sklearn-contrib so should be compatible with an sklearn pipeline.
  • [D] Good algorithm for clustering big data (sentences represented as embeddings)?
    5 projects | /r/MachineLearning | 31 Mar 2021
    Maybe use (H)DBScan which I think should work also for huge datasets. I don't think there is a ready to use clustering with unbuild cosine similarily metrics, and you also won't be able to precompute the 100k X 100k dense similarity matrix. The only way to go on this is to L2 normalize your embeddings, then the dot product will be the angular distance as a proxy to the cosine similarily. See also https://github.com/scikit-learn-contrib/hdbscan/issues/69


Posts with mentions or reviews of 100DaysofMLCode. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing hdbscan and 100DaysofMLCode you can also consider the following projects:

faiss - A library for efficient similarity search and clustering of dense vectors.

100-Days-Of-ML-Code - 100 Days of ML Coding

Top2Vec - Top2Vec learns jointly embedded topic, document and word vectors.

rmi - A learned index structure

Milvus - A cloud-native vector database, storage for next generation AI applications

rtdl - Research on Tabular Deep Learning (Python package & papers) [Moved to: https://github.com/Yura52/rtdl]

RACplusplus - A high performance implementation of Reciprocal Agglomerative Clustering in C++

vqgan-clip-generator - Implements VQGAN+CLIP for image and video generation, and style transfers, based on text and image prompts. Emphasis on ease-of-use, documentation, and smooth video creation.

homemade-machine-learning - 🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained

notebooks - Implement, demonstrate, reproduce and extend the results of the Risk articles 'Differential Machine Learning' (2020) and 'PCA with a Difference' (2021) by Huge and Savine, and cover implementation details left out from the papers.

leidenalg - Implementation of the Leiden algorithm for various quality functions to be used with igraph in Python.

GatedTabTransformer - A deep learning tabular classification architecture inspired by TabTransformer with integrated gated multilayer perceptron.