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RMTL

Regularized Multi-task Learning in R

https://github.com/transbiozi/rmtl

Science Score: 13.0%

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    Found 2 DOI reference(s) in README
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    Low similarity (9.9%) to scientific vocabulary

Keywords

low-rank-representaion multi-task-learning regularization sparse-coding
Last synced: 6 months ago · JSON representation

Repository

Regularized Multi-task Learning in R

Basic Info
Statistics
  • Stars: 18
  • Watchers: 3
  • Forks: 12
  • Open Issues: 1
  • Releases: 0
Topics
low-rank-representaion multi-task-learning regularization sparse-coding
Created almost 7 years ago · Last pushed almost 7 years ago
Metadata Files
Readme

README.md

RMTL

Regularized Multi-task Learning in R

Description

This package provides an efficient implementation of regularized multi-task learning comprising 10 algorithms applicable for regression, classification, joint feature selection, task clustering, low-rank learning, sparse learning and network incorporation. All algorithms are implemented basd on the accelerated gradient descent method and feature a complexity of O(1/k^2). Sparse model structure is induced by the solving the proximal operator. The package has been uploaded in the CRAN: https://CRAN.R-project.org/package=RMTL

Required Packages

Four packages have to be instaled in advanced to enable functions i.e. eigen-decomposition, 2D plotting: ‘MASS’, ‘psych’, ‘corpcor’ and ‘fields’. You can install them from the CRAN. R install.packages("MASS") install.packages("psych") install.packages("corpcor") install.packages("fields")

Installation

You can choose any of the three ways to install RMTL.

1) Install from CRAN in R environment (Recommend) ```R install.packages("RMTL")

in this way, the requirement for installation are automatically checked.

```

2) Install from github in R environment R install.packages("devtools") library("devtools") install_github("transbioZI/RMTL")

3) Install from the source code shell git clone https://github.com/transbioZI/RMTL.git R CMD build ./RMTL/ R CMD INSTALL RMTL*.tar.gz

Tutorial

The tutorial of multi-task learning using RMTL can be found here.

Manual

Please check "RMTL-manuel.pdf" for more details.

Reference

Cao, Han, Jiayu Zhou and Emanuel Schwarz. "RMTL: An R Library for Multi-Task Learning." Bioinformatics (2018).

Contact

If you have any question, please contact: hank9cao@gmail.com

Owner

  • Name: transbioZI
  • Login: transbioZI
  • Kind: organization

GitHub Events

Total
Last Year

Committers

Last synced: over 2 years ago

All Time
  • Total Commits: 10
  • Total Committers: 2
  • Avg Commits per committer: 5.0
  • Development Distribution Score (DDS): 0.1
Past Year
  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Hank h****o@g****m 9
hank h****o@g****m 1

Issues and Pull Requests

Last synced: over 2 years ago

All Time
  • Total issues: 3
  • Total pull requests: 0
  • Average time to close issues: 7 days
  • Average time to close pull requests: N/A
  • Total issue authors: 3
  • Total pull request authors: 0
  • Average comments per issue: 2.67
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
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Top Authors
Issue Authors
  • parisashahnazari (1)
  • armgong (1)
  • GazeLei (1)
Pull Request Authors
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Packages

  • Total packages: 1
  • Total downloads:
    • cran 647 last-month
  • Total docker downloads: 796
  • Total dependent packages: 1
  • Total dependent repositories: 2
  • Total versions: 2
  • Total maintainers: 1
cran.r-project.org: RMTL

Regularized Multi-Task Learning

  • Versions: 2
  • Dependent Packages: 1
  • Dependent Repositories: 2
  • Downloads: 647 Last month
  • Docker Downloads: 796
Rankings
Forks count: 5.8%
Stargazers count: 12.6%
Average: 16.1%
Docker downloads count: 16.1%
Dependent packages count: 18.1%
Dependent repos count: 19.3%
Downloads: 24.6%
Maintainers (1)
hank9cao@gmail.com
Last synced: 6 months ago

Dependencies

DESCRIPTION cran
  • R >= 3.5.0 depends
  • MASS >= 7.3 imports
  • corpcor >= 1.6.9 imports
  • doParallel >= 1.0.14 imports
  • foreach >= 1.4.4 imports
  • psych >= 1.8.4 imports
  • knitr * suggests
  • rmarkdown * suggests