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I am interested in evolving the 'social network' concept to a 'social organization' concept with a binary tree data structure for the organization that is created from the bottom-up, i.e. by agglomera…
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Currently no clusterers (or clustering metrics) support weighted dataset (although support for DBSCAN is proposed in #3994).
Weighting can be a compact way of representing repeated samples, and may a…
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### Please confirm if feature request does NOT exists already ?
- [X] I confirm there is no existing issue for this
### Describe the usecase for the feature
A web view like milanote or miro where w…
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#### Description
Precomputed distances are treated as "unsupported" by AgglomerativeClustering, regardless of the provenance. (e.g. sklearn.metrics.euclidean_distances)
This restriction makes it…
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I mentioned this in another issue [here](https://github.com/cvg/Hierarchical-Localization/issues/7#issuecomment-1402724284) but felt it's worth opening a separate issue since "covisibility clustering …
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Hello! Great library. I'm currently using it to cluster unlabeled images. Clustering using pca or hog did not yield good results so I extracted features for my images from a pre-trained CNN model that…
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I'm seeking some advice on managing BERTopic models for efficient topic clustering.
I've utilised BERTopic to cluster approximately 13,000 data which is three months data, resulting in around 130 …
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The paper says that to decode the binary tree from the embedding, a top-down greedy approach is used.
However from the code, it seems that still a bottom up approach is used based on the angle simil…
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As the title suggests, for some APIs like brute-force this should be as simple as flipping the direction of the k-select. For the fused algos, it'll be more complicated but not by much.
Computing the…
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Hi author, I read the pseudocode of the paper “A hierarchical clustering and data fusion approach for disease subtype discovery” you mentioned, but didn't quite understand how clusters c1 and c2 are o…