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Is there support for sparse matrices in python?
Possibly in numpy or in scipy?
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Representing a sparse matrix by a 2D array leads to wastage of lots of memory as zeroes in the matrix are of no use in most of the cases. So, instead of storing zeroes with non-zero elements, we only store non-zero elements. This means storing non-zero elements with triples- (Row, Column, value).
Sparse Matrices in PythonA dense matrix stored in a NumPy array can be converted into a sparse matrix using the CSR representation by calling the csr_matrix() function.
Sklearn has many algorithms that accept sparse matrices. The way to know is by checking the fit attribute in the documentation.
Yes.
SciPi provides scipy.sparse, a "2-D sparse matrix package for numeric data".
There are seven available sparse matrix types:
- csc_matrix: Compressed Sparse Column format
- csr_matrix: Compressed Sparse Row format
- bsr_matrix: Block Sparse Row format
- lil_matrix: List of Lists format
- dok_matrix: Dictionary of Keys format
- coo_matrix: COOrdinate format (aka IJV, triplet format)
- dia_matrix: DIAgonal format
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CVXOPT - Sparse matrices
Pysparse
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