{"id":23415310,"url":"https://github.com/mlampros/featureselection","last_synced_at":"2025-04-15T03:48:21.429Z","repository":{"id":108724269,"uuid":"59133273","full_name":"mlampros/FeatureSelection","owner":"mlampros","description":"Feature Selection in R using glmnet-lasso, xgboost and ranger ","archived":false,"fork":false,"pushed_at":"2024-08-09T14:45:19.000Z","size":154,"stargazers_count":56,"open_issues_count":0,"forks_count":27,"subscribers_count":4,"default_branch":"master","last_synced_at":"2025-04-15T03:47:59.393Z","etag":null,"topics":["feature","r","selection"],"latest_commit_sha":null,"homepage":"http://mlampros.github.io/FeatureSelection/","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/mlampros.png","metadata":{"files":{"readme":"README.md","changelog":"NEWS.md","contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null},"funding":{"github":["mlampros"],"patreon":null,"open_collective":null,"ko_fi":null,"tidelift":null,"community_bridge":null,"liberapay":null,"issuehunt":null,"otechie":null,"custom":null}},"created_at":"2016-05-18T16:32:11.000Z","updated_at":"2025-02-25T19:55:10.000Z","dependencies_parsed_at":"2025-01-06T12:26:57.257Z","dependency_job_id":"68c55861-552c-42af-b752-e06d79e95fac","html_url":"https://github.com/mlampros/FeatureSelection","commit_stats":{"total_commits":42,"total_committers":2,"mean_commits":21.0,"dds":0.4285714285714286,"last_synced_commit":"93487cb778295a1cc15574bb70c676eeb17d06a6"},"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mlampros%2FFeatureSelection","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mlampros%2FFeatureSelection/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mlampros%2FFeatureSelection/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mlampros%2FFeatureSelection/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/mlampros","download_url":"https://codeload.github.com/mlampros/FeatureSelection/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":249003941,"owners_count":21196794,"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","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":["feature","r","selection"],"created_at":"2024-12-22T21:14:40.872Z","updated_at":"2025-04-15T03:48:21.408Z","avatar_url":"https://github.com/mlampros.png","language":"R","readme":"\n[![tic](https://github.com/mlampros/FeatureSelection/workflows/tic/badge.svg?branch=master)](https://github.com/mlampros/FeatureSelection/actions)\n[![codecov.io](https://codecov.io/github/mlampros/FeatureSelection/coverage.svg?branch=master)](https://codecov.io/github/mlampros/FeatureSelection?branch=master)\n\u003ca href=\"https://www.buymeacoffee.com/VY0x8snyh\" target=\"_blank\"\u003e\u003cimg src=\"https://www.buymeacoffee.com/assets/img/custom_images/orange_img.png\" alt=\"Buy Me A Coffee\" height=\"21px\" \u003e\u003c/a\u003e\n[![](https://img.shields.io/docker/automated/mlampros/featureselection.svg)](https://hub.docker.com/r/mlampros/featureselection)\n\n\u003cbr\u003e\n\n#### Feature Selection in R using glmnet-lasso, xgboost and ranger\n\n\u003cbr\u003e\n\nThis R package wraps **glmnet-lasso**, **xgboost** and **ranger** to perform feature selection. After downloading use ? to read info about each function (i.e. ?feature_selection). More details can be found in the blog-post (http://mlampros.github.io/2016/02/14/feature-selection/). To download the latest version from Github use,\n\n\u003cbr\u003e\n\n```R\nremotes::install_github('mlampros/FeatureSelection')\n\n```\n\n\u003cbr\u003e\n\n**Package Updates**:\n\n* Currently there is a new version of *glmnet* (3.0.0) with new functionality (*relax*,  *trace*,  *assess*, *bigGlm*), however it requires an R version of 3.6.0 (see the [new vignette](https://cran.r-project.org/web/packages/glmnet/vignettes/relax.pdf)  for more information).\n* In the *ranger* R package the *ranger::importance_pvalues()* was added\n* Currently, the recommended approach for future selection is [SHAP](https://github.com/slundberg/shap)\n\n\u003cbr\u003e\n\n\n**UPDATE 03-02-2020**\n\n\u003cbr\u003e\n\n**Docker images** of the *FeatureSelection* package are available to download from my [dockerhub](https://hub.docker.com/r/mlampros/featureselection) account. The images come with *Rstudio* and the *R-development* version (latest) installed. The whole process was tested on Ubuntu 18.04. To **pull** \u0026 **run** the image do the following,\n\n\u003cbr\u003e\n\n```R\n\ndocker pull mlampros/featureselection:rstudiodev\n\ndocker run -d --name rstudio_dev -e USER=rstudio -e PASSWORD=give_here_your_password --rm -p 8787:8787 mlampros/featureselection:rstudiodev\n\n```\n\n\u003cbr\u003e\n\nThe user can also **bind** a home directory / folder to the image to use its files by specifying the **-v** command,\n\n\u003cbr\u003e\n\n```R\n\ndocker run -d --name rstudio_dev -e USER=rstudio -e PASSWORD=give_here_your_password --rm -p 8787:8787 -v /home/YOUR_DIR:/home/rstudio/YOUR_DIR mlampros/featureselection:rstudiodev\n\n\n```\n\n\u003cbr\u003e\n\nIn the latter case you might have first give permission privileges for write access to **YOUR_DIR** directory (not necessarily) using,\n\n\u003cbr\u003e\n\n```R\n\nchmod -R 777 /home/YOUR_DIR\n\n\n```\n\n\u003cbr\u003e\n\nThe **USER** defaults to *rstudio* but you have to give your **PASSWORD** of preference (see [www.rocker-project.org](https://www.rocker-project.org/) for more information).\n\n\u003cbr\u003e\n\nOpen your web-browser and depending where the docker image was *build / run* give, \n\n\u003cbr\u003e\n\n**1st. Option** on your personal computer,\n\n\u003cbr\u003e\n\n```R\nhttp://0.0.0.0:8787 \n\n```\n\n\u003cbr\u003e\n\n**2nd. Option** on a cloud instance, \n\n\u003cbr\u003e\n\n```R\nhttp://Public DNS:8787\n\n```\n\n\u003cbr\u003e\n\nto access the Rstudio console in order to give your username and password.\n\n\u003cbr\u003e\n\n","funding_links":["https://github.com/sponsors/mlampros","https://www.buymeacoffee.com/VY0x8snyh"],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmlampros%2Ffeatureselection","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmlampros%2Ffeatureselection","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmlampros%2Ffeatureselection/lists"}