Description Usage Arguments Details Value Author(s) References See Also Examples

this determines the "starting" lambda for a sequence of values for
`softImpute`

, and all nonzero solutions would require a smaller
value for `lambda`

.

1 |

`x` |
An m by n matrix. Large matrices can be in "sparseMatrix" format, as
well as "SparseplusLowRank". The latter arise after centering sparse
matrices, for example with |

The remaining arguments only apply to matrices `x`

in
`"sparseMatrix"`

, `"Incomplete"`

, or `"SparseplusLowRank"`

format.

`lambda` |
As in |

`maxit` |
maximum number of iterations. |

`trace.it` |
with |

`thresh` |
convergence threshold, measured as the relative changed in the Frobenius norm between two successive estimates. |

It is the largest singular value for the matrix,
with zeros replacing missing values. It uses `svd.als`

with
`rank=2`

.

a single number, the largest singular value

Trevor Hastie, Rahul Mazumder

Maintainer: Trevor Hastie [email protected]ford.edu

Rahul Mazumder, Trevor Hastie and Rob Tibshirani (2010)
*Spectral Regularization Algorithms for Learning Large Incomplete
Matrices*,
http://www.stanford.edu/~hastie/Papers/mazumder10a.pdf

* Journal of Machine Learning Research 11 (2010) 2287-2322*

`softImpute`

,`Incomplete`

, and `svd.als`

.

1 2 3 4 5 6 7 8 9 10 11 12 |

```
Loading required package: Matrix
Loaded softImpute 1.4
[1] 195.53
```

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