{"id":17771160,"url":"https://github.com/jeffreyevans/rfutilities","last_synced_at":"2025-03-15T15:30:25.735Z","repository":{"id":23568757,"uuid":"26936554","full_name":"jeffreyevans/rfUtilities","owner":"jeffreyevans","description":"R package for random forests model selection, inference, evaluation and validation","archived":false,"fork":false,"pushed_at":"2024-03-28T08:09:43.000Z","size":313,"stargazers_count":24,"open_issues_count":6,"forks_count":13,"subscribers_count":3,"default_branch":"master","last_synced_at":"2025-02-27T03:23:14.839Z","etag":null,"topics":["classification","cran","nonparametric-statistics","r","r-package","random-forest","regression","statistics"],"latest_commit_sha":null,"homepage":"","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/jeffreyevans.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,"governance":null,"roadmap":null,"authors":null}},"created_at":"2014-11-20T23:18:33.000Z","updated_at":"2025-01-06T08:38:49.000Z","dependencies_parsed_at":"2024-01-14T19:13:08.112Z","dependency_job_id":"7fa500b9-bacb-4c38-8ae3-bab05f7f1e61","html_url":"https://github.com/jeffreyevans/rfUtilities","commit_stats":{"total_commits":74,"total_committers":1,"mean_commits":74.0,"dds":0.0,"last_synced_commit":"a113e2c545fff7e5621a14b99583ee5002258a2d"},"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jeffreyevans%2FrfUtilities","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jeffreyevans%2FrfUtilities/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jeffreyevans%2FrfUtilities/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jeffreyevans%2FrfUtilities/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/jeffreyevans","download_url":"https://codeload.github.com/jeffreyevans/rfUtilities/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":243750401,"owners_count":20342051,"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":["classification","cran","nonparametric-statistics","r","r-package","random-forest","regression","statistics"],"created_at":"2024-10-26T21:29:42.607Z","updated_at":"2025-03-15T15:30:25.727Z","avatar_url":"https://github.com/jeffreyevans.png","language":"R","funding_links":[],"categories":[],"sub_categories":[],"readme":"# rfUtilities (CRAN 2.1-5, development 2.2-0)\n\n[![CRAN\nstatus](http://www.r-pkg.org/badges/version/rfUtilities)](https://cran.r-project.org/package=rfUtilities)\n[![CRAN RStudio mirror\ndownloads](http://cranlogs.r-pkg.org/badges/grand-total/rfUtilities)](https://cran.r-project.org/package=rfUtilities)\n\n*R package for random forests model selection, class balance and validation*\n\nRandom Forests Model Selection, inference, fit and performance evaluation\n\nrfUtilities 2.2-0 (GitHub development release) \n- added ranger random forests implementation support\n\n# Available functions in rfUtilities 2.2-0 are:\n\n| Code                         | Description                                                                             |\n|:-----------------------------|----------------------------------------------------------------------------------------|\n| `accuracy`                     | Calculates suite of accuracy statistics for classification or regression models (called by rf.crossValidation)\n| `bivariate.partialDependence`  | Bivariate partial-dependency plot\n| `collinear`                    | Evaluation of pair-wise linear or nonlinear correlations in data\n| `ensembleTest`                 | (experimental) test for degree of correlation across the ensemble, over correlation can indicate overfit\n| `logLoss`                      | Calculates Logarithmic or Likelihood loss function\n| `multi.collinear`              | Multi-collinearity test with matrix permutation.\n| `occurrence.threshold`         | A statistical sensitivity test for occurrence probability thresholds\n| `probability.calibration`      | Isotonic probability calibration\n| `ranger.proximity`             | Derives a proximity matrix for a ranger object\n| `rf.class.sensitivity`         | Random Forests class-level sensitivity analysis\n| `rf.classBalance`              | Random Forests Class Balance (Zero Inflation Correction) Model with covariance convergence\n| `rf.combine`                   | Combine Random Forests Ensembles \n| `rf.crossValidation`           | Random Forests classification or regression cross-validation, added simplified arguments and ranger support  \n| `rf.effectSize`                | Random Forests class-level parameter effect size \n| `rf.imp.freq`                  | Random Forests variable selection frequency\n| `rf.modelSel`                  | Random Forests Model Selection, simplified arguments and added ranger support\n| `rf.partial.ci`                | Random Forests regression partial dependency plot with confidence intervals\n| `rf.partial.prob`              | Random Forest probability scaled partial dependency plots\n| `rf.regression.fit`            | Evaluates fit and overfit of random forests regression models\n| `rf.significance`              | Significance test for classification or regression random forests models, simplified arguments and added ranger support \n| `rf.unsupervised`              | Unsupervised Random Forests with cluster support\n| `spatial.uncertainty`          | (experimental) creates spatial estimate of uncertainty using an Infinitesimal Jackknife to calculate standard errors  \n \n**Bugs**: Users are encouraged to report bugs here. Go to [issues](https://github.com/jeffreyevans/rfUtilities/issues) in the menu above, and press new issue to start a new bug report, documentation correction or feature request. You can direct questions to \u003cjeffrey_evans@tnc.org\u003e.\n\n**To install `rfUtilities` in R use install.packages() to download current stable release from CRAN** \n\n**or, for the development version, run the following (requires the remotes package):**\n`remotes::install_github(\"jeffreyevans/rfUtilities\")`\n\n**Tutorial**: See (http://evansmurphy.wixsite.com/evansspatial/random-forest-sdm).\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjeffreyevans%2Frfutilities","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjeffreyevans%2Frfutilities","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjeffreyevans%2Frfutilities/lists"}