make predictions from an svd object

`softImpute`

uses shrinkage when completing a matrix with
missing values. This function debiases the singular values using
ordinary least squares.

1 | ```
deBias(x, svdObject)
``` |

`x` |
matrix with missing entries, or a matrix of class |

`svdObject` |
an SVD object, the output of |

Treating the `"d"`

values as parameters, this function recomputes
them by linear regression.

An svd object is returned, with components "u", "d", and "v".

Trevor Hastie

Maintainer: Trevor Hastie hastie@stanford.edu

1 2 3 4 5 6 7 8 9 10 11 12 13 |

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