irlba (2.1.2)

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Fast Truncated SVD, PCA and Symmetric Eigendecomposition for Large Dense and Sparse Matrices.

Fast and memory efficient methods for truncated singular and eigenvalue decompositions and principal component analysis of large sparse or dense matrices.

Maintainer: B. W. Lewis
Author(s): Jim Baglama [aut, cph], Lothar Reichel [aut, cph], B. W. Lewis [aut, cre, cph]

License: GPL-3

Uses: Matrix
Reverse depends: DDRTree, s4vd, semisupKernelPCA
Reverse suggests: KernelKnn, logisticPCA, steadyICA

Released 7 months ago.

6 previous versions



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