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- Preprocessing (scala) -- test and integrate with HPC team
- Store metadata
- Tidy up clustering
- Using Kmeans
- Using DBScan
- Use resulting LDA
- Cluster users
- Cluster emails
- Visuali…
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About 'K-Means Clustering of Frozen Diffusion Features', how do you perform on the dataset? Because the LDM model accept the text input to generate the new image samples, and what do you input to obta…
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AFAICS, the k-means method **should** with a single center (and I am able to run the following command):
(Using Iris dataset as an example)
```
kmeans(rewires, centers = 1)
```
K-means clustering wi…
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### Describe the workflow you want to enable
The [GaussianMixture](https://github.com/scikit-learn/scikit-learn/blob/24f3006fb2d054b8afb26382209ae33629a8dfe0/sklearn/mixture/_gaussian_mixture.py#L4…
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Hi @borchero,
I am using the GPU for clustering or GMM and the initialization operation takes a long time compared to the CPU. After executing the following code segment on the RTX3090, the GPU initi…
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When I run command `CUDA_VISIBLE_DEVICES=0 python scripts/localagg.py ./config/imagenet_la.json` to do LA training, I get the following error :
> > LocalAggregation-Pytorch/src/objectives/localagg…
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Hi.
I am using ORB features instead of SIFT features.
I am facing an issue while performing clustering on the images.
Please find the code snippet.
``
# Create feature extraction and keypoin…
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**Migrated from Gitea**
> In #2 a
>
> submodule that checks if an object is usable for a certain kind of clustering
>
> was requested.
> So far, both HCA and KMeans require plain MxN num…
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In the docs (below), the `kmeans` algorithm takes a matrix where each column X[:, i] corresponds to an observed sample. This implementation goes against the idea of [tidy data](https://www.jstatsoft.o…
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Discussed with @ogrisel yesterday that it would be nice to subsample the data before applying kmeans++ if the data is big, as otherwise the initialization takes longer than the clustering.
This needs…