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I have been using non-negative matrix factorization (NMF) for topic modelling (as an alternative to LDA) for a while now, but so far I have not been able to find a good R package for this. In my limit…
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The current definition of "Non negative matrix factorization":
“Non negative matrix factorization is a data transformation in which factorises a matrix and which forces that all elements must be equa…
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Initially suggested by @hadoopjax in https://github.com/Data4Democracy/discursive/issues/4
- test and implement non-negative matrix factorization using both graph and textual features as described in…
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There's a whole large body of work on dimensionality reduction which handles non linearity better - i.e. UMAP. https://umap-learn.readthedocs.io/en/latest/
Is it simple to just "drop" this in place…
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Read the following: https://www.geeksforgeeks.org/non-negative-matrix-factorization/
https://towardsdatascience.com/non-negative-matrix-factorization-for-image-compression-and-clustering-89bb0f9fa8e…
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In the initial design of the matrix package I included the error type and maybe function. There was an intention that this could be used by client code to recover from errors in a way that mimics erro…
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I am a bioinformatics PhD and I really appreciate your mlr3cluster package. This package provides many unsupervised clustering algorithms. However, I regret to find that the two most commonly used alg…
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https://link.springer.com/chapter/10.1007/978-3-540-89197-0_103