How do I transform a “SciPy sparse matrix” to a “NumPy matrix”?

Question

I am using a python function called \"incidence_matrix(G)\", which returns the incident matrix of graph. It is from Networkx package. The problem that I am facing is the ret

Answer 1

I found that in the case of csr matrices, todense() and toarray() simply wrapped the tuples rather than producing a ndarray formatted version of the data in matrix form. This was unusable for the skmultilearn classifiers I'm training.

I translated it to a lil matrix- a format numpy can parse accurately, and then ran toarray() on that:

sparse.lil_matrix().toarray()