Package: softImpute
Type: Package
Title: matrix completion via iterative soft-thresholded svd
Version: 1.0
Date: 2013-03-30
Author: Trevor Hastie <hastie@stanford.edu> and Rahul Mazumder
        <rahul.mazumder@gmail.com>
Maintainer: Trevor Hastie <hastie@stanford.edu>
Description: Iterative methods for matrix completion that use
        nuclear-norm regularization. There are two main approaches.The
        one approach uses iterative soft-thresholded svds to impute the
        missing values. The second approach uses alternating least
        squares. Both have an "EM" flavor, in that at each iteration
        the matrix is completed with the current estimate. For large
        matrices there is a special sparse-matrix class named
        "Incomplete" that efficiently handles all computations. The
        package includes procedures for centering and scaling rows,
        columns or both.
License: GPL-2
LazyLoad: yes
Depends: Matrix, methods
Packaged: 2013-04-02 20:03:55 UTC; hastie
NeedsCompilation: yes
Repository: CRAN
Date/Publication: 2013-04-03 07:17:36
