{"id":20693430,"url":"https://github.com/nanxstats/enpls","last_synced_at":"2025-04-22T17:42:55.118Z","repository":{"id":21452661,"uuid":"24771056","full_name":"nanxstats/enpls","owner":"nanxstats","description":"Algorithmic framework for measuring feature importance, outlier detection, model applicability evaluation, and ensemble predictive modeling with (sparse) partial least squares regressions.","archived":false,"fork":false,"pushed_at":"2021-12-21T03:56:32.000Z","size":28882,"stargazers_count":18,"open_issues_count":0,"forks_count":8,"subscribers_count":4,"default_branch":"master","last_synced_at":"2025-04-18T20:31:52.458Z","etag":null,"topics":["chemometrics","dimensionality-reduction","ensemble-learning","machine-learning","outlier-detection","partial-least-squares-regression"],"latest_commit_sha":null,"homepage":"https://nanx.me/enpls/","language":"R","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/nanxstats.png","metadata":{"files":{"readme":"README.Rmd","changelog":null,"contributing":"CONTRIBUTING.md","funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2014-10-03T19:33:03.000Z","updated_at":"2023-01-07T17:17:10.000Z","dependencies_parsed_at":"2022-08-21T13:40:34.431Z","dependency_job_id":null,"html_url":"https://github.com/nanxstats/enpls","commit_stats":null,"previous_names":[],"tags_count":6,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/nanxstats%2Fenpls","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/nanxstats%2Fenpls/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/nanxstats%2Fenpls/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/nanxstats%2Fenpls/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/nanxstats","download_url":"https://codeload.github.com/nanxstats/enpls/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":250289341,"owners_count":21405954,"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":["chemometrics","dimensionality-reduction","ensemble-learning","machine-learning","outlier-detection","partial-least-squares-regression"],"created_at":"2024-11-16T23:26:36.948Z","updated_at":"2025-04-22T17:42:55.093Z","avatar_url":"https://github.com/nanxstats.png","language":"R","funding_links":[],"categories":[],"sub_categories":[],"readme":"---\noutput: github_document\n---\n\n\u003c!-- README.md is generated from README.Rmd. Please edit that file --\u003e\n\n```{r, include = FALSE}\nknitr::opts_chunk$set(\n  collapse = TRUE,\n  comment = \"#\u003e\",\n  fig.path = \"man/figures/README-\",\n  out.width = \"100%\"\n)\n```\n\n# enpls \u003cimg src=\"man/figures/logo.png\" align=\"right\" width=\"120\" /\u003e\n\n\u003c!-- badges: start --\u003e\n[![R-CMD-check](https://github.com/nanxstats/enpls/workflows/R-CMD-check/badge.svg)](https://github.com/nanxstats/enpls/actions)\n[![CRAN Version](https://www.r-pkg.org/badges/version/enpls)](https://cran.r-project.org/package=enpls)\n[![Downloads from the RStudio CRAN mirror](https://cranlogs.r-pkg.org/badges/enpls)](https://cranlogs.r-pkg.org/badges/enpls)\n\u003c!-- badges: end --\u003e\n\n`enpls` offers an algorithmic framework for measuring feature importance, outlier detection, model applicability domain evaluation, and ensemble predictive modeling with (sparse) partial least squares regressions.\n\n## Installation\n\nYou can install `enpls` from CRAN:\n\n```r\ninstall.packages(\"enpls\")\n```\n\nOr try the development version on GitHub:\n\n```r\nremotes::install_github(\"nanxstats/enpls\")\n```\n\nSee `vignette(\"enpls\")` for a quick-start guide.\n\n## Gallery\n\n### Feature importance\n\n![](man/figures/feature-importance.png)\n\n### Outlier detection\n\n![](man/figures/outlier-detection.png)\n\n### Model applicability domain evaluation and ensemble predictive modeling\n\n![](man/figures/ensemble-modeling.png)\n\n## Contribute\n\nTo contribute to this project, please take a look at the [Contributing Guidelines](CONTRIBUTING.md) first. Please note that this project is released with a [Contributor Code of Conduct](CONDUCT.md). By participating in this project you agree to abide by its terms.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnanxstats%2Fenpls","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fnanxstats%2Fenpls","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnanxstats%2Fenpls/lists"}