{"id":32207865,"url":"https://github.com/transbiozi/rmtl","last_synced_at":"2025-10-22T06:00:02.176Z","repository":{"id":56937006,"uuid":"173581659","full_name":"transbioZI/RMTL","owner":"transbioZI","description":"Regularized Multi-task Learning in R","archived":false,"fork":false,"pushed_at":"2019-03-25T19:04:54.000Z","size":339,"stargazers_count":19,"open_issues_count":1,"forks_count":12,"subscribers_count":2,"default_branch":"master","last_synced_at":"2025-10-22T05:59:49.632Z","etag":null,"topics":["low-rank-representaion","multi-task-learning","regularization","sparse-coding"],"latest_commit_sha":null,"homepage":"https://CRAN.R-project.org/package=RMTL","language":"R","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/transbioZI.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2019-03-03T13:56:53.000Z","updated_at":"2024-03-21T11:28:23.000Z","dependencies_parsed_at":"2022-08-21T01:10:27.453Z","dependency_job_id":null,"html_url":"https://github.com/transbioZI/RMTL","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/transbioZI/RMTL","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/transbioZI%2FRMTL","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/transbioZI%2FRMTL/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/transbioZI%2FRMTL/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/transbioZI%2FRMTL/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/transbioZI","download_url":"https://codeload.github.com/transbioZI/RMTL/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/transbioZI%2FRMTL/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":280389301,"owners_count":26322507,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","status":"online","status_checked_at":"2025-10-22T02:00:06.515Z","response_time":63,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["low-rank-representaion","multi-task-learning","regularization","sparse-coding"],"created_at":"2025-10-22T05:59:52.499Z","updated_at":"2025-10-22T06:00:02.162Z","avatar_url":"https://github.com/transbioZI.png","language":"R","funding_links":[],"categories":[],"sub_categories":[],"readme":"# RMTL\nRegularized Multi-task Learning in R\n\n# Description \nThis 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\n\n# Required Packages\nFour 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.\n```R\ninstall.packages(\"MASS\")\ninstall.packages(\"psych\")\ninstall.packages(\"corpcor\")\ninstall.packages(\"fields\")\n```\n\n# Installation\nYou can choose any of the three ways to install RMTL.\n\n1) Install from CRAN in R environment (Recommend)\n```R\ninstall.packages(\"RMTL\")\n# in this way, the requirement for installation are automatically checked.\n```\n\n2) Install from github in R environment\n```R\ninstall.packages(\"devtools\")\nlibrary(\"devtools\")\ninstall_github(\"transbioZI/RMTL\")\n```\n\n3) Install from the source code \n```shell\ngit clone https://github.com/transbioZI/RMTL.git\nR CMD build ./RMTL/\nR CMD INSTALL RMTL*.tar.gz\n```\n\n# Tutorial\nThe tutorial of multi-task learning using RMTL can be found [here](https://cran.r-project.org/web/packages/RMTL/vignettes/rmtl.html).\n\n# Manual\nPlease check [\"RMTL-manuel.pdf\"](https://cran.r-project.org/web/packages/RMTL/RMTL.pdf) for more details.\n\n# Reference\n[Cao, Han, Jiayu Zhou and Emanuel Schwarz. \"RMTL: An R Library for Multi-Task Learning.\" Bioinformatics (2018).](https://doi.org/10.1093/bioinformatics/bty831)\n\n\n# Contact\nIf you have any question, please contact: hank9cao@gmail.com\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftransbiozi%2Frmtl","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftransbiozi%2Frmtl","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftransbiozi%2Frmtl/lists"}