{"id":28314890,"url":"https://github.com/ramhiser/sparsediscrim","last_synced_at":"2025-06-23T17:31:29.870Z","repository":{"id":1117644,"uuid":"988565","full_name":"ramhiser/sparsediscrim","owner":"ramhiser","description":"Sparse and Regularized Discriminant Analysis in R","archived":false,"fork":false,"pushed_at":"2020-11-15T20:08:12.000Z","size":609,"stargazers_count":14,"open_issues_count":6,"forks_count":5,"subscribers_count":3,"default_branch":"master","last_synced_at":"2025-06-01T07:21:05.484Z","etag":null,"topics":["classifier","high-dimensional-data","machine-learning","r"],"latest_commit_sha":null,"homepage":"","language":"R","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"other","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/ramhiser.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2010-10-14T23:38:21.000Z","updated_at":"2024-11-12T14:57:31.000Z","dependencies_parsed_at":"2022-08-16T12:05:16.618Z","dependency_job_id":null,"html_url":"https://github.com/ramhiser/sparsediscrim","commit_stats":null,"previous_names":[],"tags_count":5,"template":false,"template_full_name":null,"purl":"pkg:github/ramhiser/sparsediscrim","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ramhiser%2Fsparsediscrim","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ramhiser%2Fsparsediscrim/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ramhiser%2Fsparsediscrim/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ramhiser%2Fsparsediscrim/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ramhiser","download_url":"https://codeload.github.com/ramhiser/sparsediscrim/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ramhiser%2Fsparsediscrim/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":261522510,"owners_count":23171833,"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":["classifier","high-dimensional-data","machine-learning","r"],"created_at":"2025-05-24T20:09:50.342Z","updated_at":"2025-06-23T17:31:29.833Z","avatar_url":"https://github.com/ramhiser.png","language":"R","funding_links":[],"categories":[],"sub_categories":[],"readme":"# sparsediscrim\n\n[![Build Status](https://travis-ci.org/ramhiser/sparsediscrim.svg?branch=master)](https://travis-ci.org/ramhiser/sparsediscrim)\n\nThe R package `sparsediscrim` provides a collection of sparse and regularized discriminant\nanalysis classifiers that are especially useful for when applied to\nsmall-sample, high-dimensional data sets.\n\n## Installation\n\nYou can install the stable version on [CRAN](https://cran.r-project.org/package=sparsediscrim):\n\n```r\ninstall.packages('sparsediscrim', dependencies = TRUE)\n```\n\nIf you prefer to download the latest version, instead type:\n\n```r\nlibrary(devtools)\ninstall_github('ramhiser/sparsediscrim')\n```\n\n## Classifiers\n\nThe `sparsediscrim` package features the following classifier (the R function\nis included within parentheses):\n\n* [High-Dimensional Regularized Discriminant Analysis](https://arxiv.org/abs/1602.01182) (`hdrda`) from Ramey et al. (2015)\n\nThe `sparsediscrim` package also includes a variety of additional classifiers\nintended for small-sample, high-dimensional data sets. These include:\n\n| Classifier                                                    | Author                                                                                             | R Function |\n|---------------------------------------------------------------|----------------------------------------------------------------------------------------------------|------------|\n| Diagonal Linear Discriminant Analysis                         | [Dudoit et al. (2002)](http://www.tandfonline.com/doi/abs/10.1198/016214502753479248)              | `dlda`     |\n| Diagonal Quadratic Discriminant Analysis                      | [Dudoit et al. (2002)](http://www.tandfonline.com/doi/abs/10.1198/016214502753479248)              | `dqda`     |\n| Shrinkage-based Diagonal Linear Discriminant Analysis         | [Pang et al. (2009)](http://onlinelibrary.wiley.com/doi/10.1111/j.1541-0420.2009.01200.x/abstract) | `sdlda`    |\n| Shrinkage-based Diagonal Quadratic Discriminant Analysis      | [Pang et al. (2009)](http://onlinelibrary.wiley.com/doi/10.1111/j.1541-0420.2009.01200.x/abstract) | `sdqda`    |\n| Shrinkage-mean-based Diagonal Linear Discriminant Analysis    | [Tong et al. (2012)](http://bioinformatics.oxfordjournals.org/content/28/4/531.long)               | `smdlda`   |\n| Shrinkage-mean-based Diagonal Quadratic Discriminant Analysis | [Tong et al. (2012)](http://bioinformatics.oxfordjournals.org/content/28/4/531.long)               | `smdqda`   |\n| Minimum Distance Empirical Bayesian Estimator (MDEB)          | [Srivistava and Kubokawa (2007)](http://www.utstat.utoronto.ca/~srivasta/exp1.pdf)                 | `mdeb`     |\n| Minimum Distance Rule using Modified Empirical Bayes (MDMEB)  | [Srivistava and Kubokawa (2007)](http://www.utstat.utoronto.ca/~srivasta/exp1.pdf)                 | `mdmeb`    |\n| Minimum Distance Rule using Moore-Penrose Inverse (MDMP)      | [Srivistava and Kubokawa (2007)](http://www.utstat.utoronto.ca/~srivasta/exp1.pdf)                 | `mdmp`     |\n\nWe also include modifications to Linear Discriminant Analysis (LDA) with\nregularized covariance-matrix estimators:\n\n* Moore-Penrose Pseudo-Inverse (`lda_pseudo`)\n* Schafer-Strimmer estimator (`lda_schafer`)\n* Thomaz-Kitani-Gillies estimator (`lda_thomaz`)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Framhiser%2Fsparsediscrim","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Framhiser%2Fsparsediscrim","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Framhiser%2Fsparsediscrim/lists"}