Factors a matrix into rank-k left and right factors with their singular values, optionally centering the columns first, and states what the compression actually cost: the Frobenius reconstruction error against the input and the fraction of spectral energy retained. The full spectrum comes back too, so a caller can pick a different k without a second call. With centering enabled this is principal component analysis, and the column means are returned as part of the model.

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