| Name : R-ECLRMC
| |
| Version : 1.0
| Vendor : obs://build_opensuse_org/devel:languages:R
|
| Release : lp153.2.13
| Date : 2024-06-14 11:14:34
|
| Group : Development/Libraries/Other
| Source RPM : R-ECLRMC-1.0-lp153.2.13.src.rpm
|
| Size : 0.03 MB
| |
| Packager : (none)
| |
| Summary : Ensemble Correlation-Based Low-Rank Matrix Completion
|
Description :
Ensemble correlation-based low-rank matrix completion method (ECLRMC)
is an extension to the LRMC based methods. Traditionally, the LRMC
based methods give identical importance to the whole data which results
in emphasizing on the commonality of the data and overlooking the
subtle but crucial differences. This method aims to overcome the
equality assumption problem that exists in the current LRMS based
methods. Ensemble correlation-based low-rank matrix completion (ECLRMC)
takes consideration of the specific characteristic of each sample and
performs LRMC on the set of samples with a strong correlation. It uses
an ensemble learning method to improve the imputation performance.
Since each sample is analyzed independently this method can be
parallelized by distributing imputation across many computation units
or GPU platforms. This package provides three different methods (LRMC,
CLRMC and ECLRMC) for data imputation. There is also an NRMS function
for evaluating the result. Chen, Xiaobo, et al (2017)
< doi:10.1016/j.knosys.2017.06.010>.
|
RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Leap_15.3/x86_64 |
