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Home Page: https://michalovadek.github.io/nmfbin/
License: Other
Non-Negative Matrix Factorization for Binary Data
Home Page: https://michalovadek.github.io/nmfbin/
License: Other
would be interesting to make some comparisons with methods where factorized matrices are constrained to be binary (in standard NMF components are positive real-valued). There is a package for this: https://cran.r-project.org/web/packages/rBMF/index.html
the input matrix should be converted to (1) Matrix::sparseMatrix
or equivalent and (2) logical (if integer). Should allow for more efficient computation
clipping should be worse but is it?
as specified eg here: https://www.scitepress.org/papers/2015/56148/56148.pdf
passing a data frame should either:
preferably 1)?
implement SOTA initialization features (Spectral, etc.). Pretty sure svd is not working properly in 0.1.0
this should be a separate vignette
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