Sparsity is a measured way of optimizing machine learning models by deliberately specifying which nodes are composed of zero values.
Sparse models, as opposed to dense models, contain mostly zero values. This is different to models which have missing values, because in the case of a sparse model the zero values are known, but contain no numerical values.
