Performing Decomposition on Sparse Matrices in Python
Even the input matrix is sparse the output will not be a sparse matrix.  If the system does not support a dense matrix neither the results will not be supported
I'm trying to decomposing signals in components (matrix factorization) in a large sparse matrix in Python using the sklearn library. 
I made use of scipy's scipy.sparse.csc_matrix to construct my matrix of data. However I'm unable to perform any analysis such as factor analysis or independent component analysis. The only thing I'm able to do is use truncatedSVD or scipy's scipy.sparse.linalg.svds and perform PCA.
Does anyone know any work-arounds to doing ICA or FA on a sparse matrix in python? Any help would be much appreciated! Thanks.