Sparse Matrix Representation in Python - KDnuggets

Most machine learning practitioners are accustomed to adopting a matrix representation of their datasets prior to feeding the data into a machine learning algorithm. Matrices are an ideal form for this, usually with rows representing dataset instances and columns representing features. A sparse matrix is a matrix in which most elements are zeroes. This is in contrast to a dense matrix, the differentiating characteristic of which you can likely figure out at this point without any help. Often our data is dense, with feature columns filled up for every instance we have.