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This paper suggests a k-means seeding method that is much faster than kmeans++ and nearly as good. The algorithm constructs a Markov chain on the data points, and in practice k-1 chains of length 100 …
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Hello,
I'm using a dataset composed of genes (row) and patient (column), I'm creating the heatmap but then I want to find and save the kmean's values of each samples present in my heatmap. Is it po…
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I use K-Means to do binary data split. However I have to handle the following cases by myself:
1) if the sample count is less or equal than number of clusters (two, one or zero)
2) in case all sample…
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I found that your k-means doesn't work well.
I think you may misunderstand the updating part of k-means, which is that your should use
the whole data set to locate the new central point, rather th…
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oke
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![Screenshot 2024-02-15 at 5 35 07 PM](https://github.com/BorisovNM/Shambhala2/assets/143759952/c53f9904-a8eb-4a20-af82-21215a9ee8a3)
Hello .. I am trying to use Shambhala2 for normalizing a datase…
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`_align_images_to_template` instantiates a bunch of `PairwiseAlignment` estimators, each of which generate their own parcellation of the data. I would argue that a single parcellation should be comput…
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In the section "Beyond the Basics: Training and predicting with just the conditional density or just with clustering"
when I run the following code:
```
#we'll use the same dataset2 from above …
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## Reproduce
```python
from fast_pytorch_kmeans import MultiKMeans
from collections import Counter
kmeans = MultiKMeans(n_clusters=50, mode='euclidean', verbose=1)
x = torch.randn(1000, 200, …
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When using the `Kmeans` function, there are times when the program just hangs. Cannot reproduce deterministically because it only happens sometimes. but the following code hangs sometimes and require…