{"id":15646335,"url":"https://github.com/ianstenbit/arulescba","last_synced_at":"2026-03-06T17:03:04.157Z","repository":{"id":65921248,"uuid":"58610368","full_name":"ianstenbit/arulesCBA","owner":"ianstenbit","description":"Classification Based on Association Rules in R","archived":false,"fork":false,"pushed_at":"2022-11-05T22:30:01.000Z","size":990,"stargazers_count":50,"open_issues_count":3,"forks_count":15,"subscribers_count":4,"default_branch":"master","last_synced_at":"2025-04-30T12:20:48.845Z","etag":null,"topics":["algorithm","association-rules","cba","classification","cran","r"],"latest_commit_sha":null,"homepage":"","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/ianstenbit.png","metadata":{"files":{"readme":"README.Rmd","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":"2016-05-12T05:26:05.000Z","updated_at":"2025-04-03T01:44:56.000Z","dependencies_parsed_at":"2023-02-16T10:15:30.368Z","dependency_job_id":null,"html_url":"https://github.com/ianstenbit/arulesCBA","commit_stats":null,"previous_names":["ianjjohnson/arulescba"],"tags_count":2,"template":false,"template_full_name":null,"purl":"pkg:github/ianstenbit/arulesCBA","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ianstenbit%2FarulesCBA","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ianstenbit%2FarulesCBA/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ianstenbit%2FarulesCBA/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ianstenbit%2FarulesCBA/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ianstenbit","download_url":"https://codeload.github.com/ianstenbit/arulesCBA/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ianstenbit%2FarulesCBA/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":30186780,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-03-06T14:42:24.748Z","status":"ssl_error","status_checked_at":"2026-03-06T14:42:14.925Z","response_time":250,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.6:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"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":["algorithm","association-rules","cba","classification","cran","r"],"created_at":"2024-10-03T12:12:28.971Z","updated_at":"2026-03-06T17:02:59.146Z","avatar_url":"https://github.com/ianstenbit.png","language":"R","funding_links":[],"categories":[],"sub_categories":[],"readme":"---\ntitle: \"R package arulesCBA: Classification Based on Association Rules\"\noutput: github_document\n---\n\n```{r echo=FALSE}\noptions(digits = 2)\nknitr::opts_chunk$set(tidy = TRUE, message = FALSE)\n```\n\n```{r echo=FALSE, results = 'asis'}\npkg \u003c- 'arulesCBA'\n\nlibrary(stringr)\n\n  cat(str_interp(\"[![CRAN version](http://www.r-pkg.org/badges/version/${pkg})](https://CRAN.R-project.org/package=${pkg})\\n\"))\n  cat(str_interp(\"[![stream r-universe status](https://mhahsler.r-universe.dev/badges/${pkg})](https://mhahsler.r-universe.dev/ui#package:${pkg})\\n\"))\n  cat(str_interp(\"[![CRAN RStudio mirror downloads](http://cranlogs.r-pkg.org/badges/grand-total/${pkg})](https://CRAN.R-project.org/package=${pkg})\\n\"))\n```\n\n\nThe R package [arulesCBA](https://cran.r-project.org/package=arulesCBA) (Hahsler et al, 2020) \nis an extension of the package [arules](https://cran.r-project.org/package=arules) to perform\nassociation rule-based classification. The package provides the infrastructure for class association rules and implements associative classifiers based on the following algorithms:\n\n* __CBA__:    Classification Based on Association Rules (Liu et al, 1998).\n* __CMAR__:   Classification based on Multiple Association Rule  (Li, Han and Pei, 2001) via LUCS-KDD Software Library.\n* __CPAR__:   Classification based on Predictive Association Rules (Yin and Han, 2003) via LUCS-KDD Software Library.\n* __C4.5__:   Rules extracted from a C4.5 decision tree (Quinlan, 1993) via J48 in R/Weka.\n* __FOIL__:   First-Order Inductive Learner (Yin and Han, 2003).\n* __PART__:   Rules from Partial Decision Trees (Frank and Witten, 1998) via R/Weka.\n* __PRM__:    Predictive Rule Mining (Yin and Han, 2003) via LUCS-KDD Software Library.\n* __RCAR__:   Regularized Class Association Rules using Logistic Regression (Azmi et al, 2019).\n* __RIPPER__: Repeated Incremental Pruning to Produce Error Reduction (Cohen, 1995) via R/Weka.\n\nThe package also provides the infrastructure for associative classification (supervised discetization, mining class association rules (CARs)), and implements various association rule-based classification strategies\n(first match, majority voting, weighted voting, etc.).\n\n## Installation\n\n__Stable CRAN version:__ install from within R with\n```{r eval=FALSE}\ninstall.packages(\"arulesCBA\")\n```\n\n__Current development version:__ Install from [r-universe.](https://mhahsler.r-universe.dev/ui#package:arulesCBA)\n\n## Usage\n\n```{r}\nlibrary(\"arulesCBA\")\ndata(\"iris\")\n```\n\nLearn a classifier.\n\n```{r}\nclassifier \u003c- CBA(Species ~ ., data = iris)\nclassifier\n```\n\nInspect the rulebase.\n\n```{r}\ninspect(rules(classifier), linebreak = TRUE)\n```\n  \nMake predictions for the first few instances of iris.\n\n```{r}\npredict(classifier, head(iris))\n```\n\n## References\n\n* M. Hahsler, I. Johnson, T. Kliegr and J. Kuchar (2019). [Associative Classification in R: arc, arulesCBA, and rCBA](https://journal.r-project.org/archive/2019/RJ-2019-048/). _The R Journal_ 11(2), pp. 254-267.\n* M. Azmi, G.C. Runger, and A. Berrado (2019). Interpretable regularized class association rules algorithm for classification in a categorical data space. _Information Sciences,_ Volume 483, May 2019, pp. 313-331.\n* W. W. Cohen (1995). Fast effective rule induction. In A. Prieditis and S. Russell (eds.), _Proceedings of the 12th International Conference on Machine Learning,_ pp. 115-123. Morgan Kaufmann. ISBN 1-55860-377-8.\n* E. Frank and I. H. Witten (1998). Generating accurate rule sets without global optimization. In J. Shavlik (ed.), _Machine Learning: Proceedings of the Fifteenth International Conference,_ Morgan Kaufmann Publishers: San Francisco, CA.\n* W. Li, J. Han and J. Pei (2001). CMAR: accurate and efficient classification based on multiple class-association rules, _Proceedings 2001 IEEE International Conference on Data Mining,_ San Jose, CA, USA, pp. 369-376.\n* B. Liu, W. Hsu and Y. Ma (1998). Integrating Classification and Association Rule Mining. _KDD'98 Proceedings of the Fourth International Conference on Knowledge Discovery and Data Mining,_ New York, AAAI, pp. 80-86.\n* R. Quinlan (1993). _C4.5: Programs for Machine Learning._ Morgan Kaufmann Publishers, San Mateo, CA.\n* X. Yin and J. Han (2003). CPAR: Classification based on Predictive Association Rules, _Proceedings of the 2003 SIAM International Conference on Data Minin,_ pp. 331-235.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fianstenbit%2Farulescba","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fianstenbit%2Farulescba","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fianstenbit%2Farulescba/lists"}