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ECLRMC
View on CRAN: Click
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Download and install ECLRMC package within the R console
Install from CRAN:
install.packages("ECLRMC")
Install from Github:
library("remotes")
install_github("cran/ECLRMC")
Install by package version:
library("remotes")
install_version("ECLRMC", "1.0")
Attach the package and use:
library("ECLRMC")
Maintained by
Mahdi Ghadamyari
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-08-31
Latest Update: 2018-08-31
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) .
How to cite:
Mahdi Ghadamyari (2018). ECLRMC: Ensemble Correlation-Based Low-Rank Matrix Completion. R package version 1.0, https://cran.r-project.org/web/packages/ECLRMC
Previous versions and publish date:
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Functions, R codes and Examples using
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Some associated functions: CLRMC . ECLRMC . LRMC . NRMS .
Some associated R codes: ECLRMC.R . Full ECLRMC package functions and examples
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