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A data matrix is approximated as the product of two matrices. By construction, the resulting approximation is of lower algebraic rank. The data matrix A may contain features of different data-types and missing entries, as illustrated here. Each row of X is an encoding of an observation in A in the latent feature space. Each column of Y is an encoding of a feature of A in the latent feature space.
