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What was the strategic reason as to why spectral clustering was used in the Pavlovic paper? Can someone give me a brief overview of how spectral clustering works and how it differs from some of the o…
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- Implement K Means Clustering to compress image
- pls include visualization of original colour space and reduced dimension colour space after compression
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I have been trying simple K-Means clustering, and always clusters into 1-cluster. Here is the data set to be clustered.
/**
\* The data to be clustered.
*/
public static final double[][…
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The K-Means clustering algorithm is an important clustering algorithm used in Vector Quantization. It is to be coded in Java and Python and its inbuilt implementations have to be looked at.
@syedmuna…
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Add k-means[1] clustering to doddle-model.
* Select the algorithm implementation (Lloyd's, Hartigan-Wong, ...)
* Implement initialisation methods (Random, k-means++)
* Include parallelization
…
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A wonderful work!
I have a question regarding the implementation of the cluster center calculation. In the original paper, the HSF module is described as follows:
_The HSF module follows a three-s…
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Thank you for the great work! I was wondering if you have tried checking the quality of the assignment clusters using FAISS K-Means. I attempted a similar approach to your code by training FAISS K-Mea…
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```
What steps will reproduce the problem?
1. I have 136 documents in docvectors.bin and I have run this command:-
java pitt.search.semanticvectors.ClusterResults -numclusters 4 docvectors.bin
2. Alth…
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```
What steps will reproduce the problem?
1. I have 136 documents in docvectors.bin and I have run this command:-
java pitt.search.semanticvectors.ClusterResults -numclusters 4 docvectors.bin
2. Alth…
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Regime Detection . This shows a simple example of how to detect regime changes for financial data.
We apply the K-means clustering method. We use the elbow method to identify the optimal number of …