For questions about spectral clustering techniques, which make use of the spectrum (eigenvalues) of the similarity matrix of the data to perform dimensionality reduction before clustering in fewer dimensions.
Questions tagged [spectral-clustering]
4 questions
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What are the benefits of using spectral k-means over simple k-means?
I have understood why k-means can get stuck in local minima.
Now, I am curious to know how the spectral k-means helps to avoid this local minima problem.
According to this paper A tutorial on Spectral, The spectral algorithm goes in the following…
Amartya
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How are GCN doing semi-supervised learning?
In Semi-Supervised Classification with Graph Convolutional Networks, the authors say that GCN is an approach for semi-supervised learning (SSL).
But a GCN is making predictions using only the graph Laplacian. The single place where I find the labels…
willtryagain
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Speech diarization for a conversation detector: A good idea or not?
I am trying to write a program in which an ai can detect whether a conversation is occurring or not. The ai does not need to transcribe words or have any meaning about the conversation, simply if one is occurring. A conversation can then simply be…
0
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2 answers
Why does k-means have more bias than spectral clustering and GMM?
I ran into a 2019-Entrance Exam question as follows:
The answer mentioned is (4), but some search on google showed me maybe (1) and (2) is equal to (4). Why would k-means be the algorithm with the highest bias? (Can you please also provide…
