Description
Nonnegative matrix factorization (NMF) is a technique to factorize a matrix with nonnegative values into the product of two matrices. Covariates are also allowed. Parallel computing is an option to enhance the speed and high-dimensional and large scale (and/or sparse) data are allowed. Relevant papers include: Wang Y. X. and Zhang Y. J. (2012). Nonnegative matrix factorization: A comprehensive review. IEEE Transactions on Knowledge and Data Engineering, 25(6): 1336-1353 <doi:10.1109/TKDE.2012.51> and Kim H. and Park H. (2008). Nonnegative matrix factorization based on alternating nonnegativity constrained least squares and active set method. SIAM Journal on Matrix Analysis and Applications, 30(2): 713-730 <doi:10.1137/07069239X>.
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Check details (2 non-OK)
installed package size
installed size is 7.4Mb
sub-directories of 1Mb or more:
libs 7.2Mb
installed package size
installed size is 7.5Mb
sub-directories of 1Mb or more:
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Check History
NOTE 13 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 17, 2026
installed package size
installed size is 7.4Mb
sub-directories of 1Mb or more:
libs 7.2Mb
OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 11, 2026
ERROR 13 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE Mar 10, 2026
examples
Running examples in ‘nnmf-Ex.R’ failed The error most likely occurred in: > ### Name: nmfqp.reg > ### Title: NMF with covariates minimizing the Frobenius norm > ### Aliases: nmfqp.reg > > ### ** Examples > > x <- as.matrix(iris[, 1:3]) > z <- model.matrix(x ~., data = iris[, 4:5])[, -1] > mod <- nmfqp.reg(x, z, 2) Error in quadprog::solve.QP(Dmat, dvec, dk, b0k) : constraints are inconsistent, no solution! Calls: nmfqp.reg -> <Anonymous> Execution halted