{"id":17218290,"url":"https://github.com/pbiecek/breakdown","last_synced_at":"2025-04-09T12:07:11.977Z","repository":{"id":56935304,"uuid":"111193301","full_name":"pbiecek/breakDown","owner":"pbiecek","description":"Model Agnostics breakDown plots","archived":false,"fork":false,"pushed_at":"2024-03-12T21:20:53.000Z","size":21166,"stargazers_count":103,"open_issues_count":7,"forks_count":16,"subscribers_count":11,"default_branch":"master","last_synced_at":"2025-04-02T03:38:01.628Z","etag":null,"topics":["data-science","iml","interpretability","machine-learning","visual-explanations","xai"],"latest_commit_sha":null,"homepage":"https://pbiecek.github.io/breakDown/","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/pbiecek.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}},"created_at":"2017-11-18T09:37:00.000Z","updated_at":"2024-12-04T12:44:03.000Z","dependencies_parsed_at":"2024-10-31T03:13:20.302Z","dependency_job_id":null,"html_url":"https://github.com/pbiecek/breakDown","commit_stats":{"total_commits":92,"total_committers":6,"mean_commits":"15.333333333333334","dds":0.25,"last_synced_commit":"8a43b05edc8d78fcc1303dd0e3c5b85be2c0e52c"},"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pbiecek%2FbreakDown","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pbiecek%2FbreakDown/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pbiecek%2FbreakDown/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pbiecek%2FbreakDown/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/pbiecek","download_url":"https://codeload.github.com/pbiecek/breakDown/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248036067,"owners_count":21037092,"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":["data-science","iml","interpretability","machine-learning","visual-explanations","xai"],"created_at":"2024-10-15T03:46:03.824Z","updated_at":"2025-04-09T12:07:11.955Z","avatar_url":"https://github.com/pbiecek.png","language":"R","readme":"[![CRAN_Status_Badge](http://www.r-pkg.org/badges/version/breakDown)](https://cran.r-project.org/package=breakDown)\n[![Downloads](http://cranlogs.r-pkg.org/badges/breakDown)](http://cran.rstudio.com/package=breakDown)\n[![Total Downloads](http://cranlogs.r-pkg.org/badges/grand-total/breakDown?color=orange)](http://cranlogs.r-pkg.org/badges/grand-total/breakDown)\n[![Build Status](https://api.travis-ci.org/pbiecek/breakDown.png)](https://travis-ci.org/pbiecek/breakDown)\n[![Coverage\nStatus](https://img.shields.io/codecov/c/github/pbiecek/breakDown/master.svg)](https://codecov.io/github/pbiecek/breakDown?branch=master)\n\n# Break Down: Model Agnostic Explainers for Individual Predictions\n\nThe `breakDown` package is a model agnostic tool for decomposition of predictions from black boxes.\nBreak Down Table shows contributions of every variable to a final prediction. \nBreak Down Plot presents variable contributions in a concise graphical way. \nThis package works for binary classifiers and general regression models. \n\nFind lots of R examples at `breakDown` website: https://pbiecek.github.io/breakDown/\n\nInterested in the methodology? Find the math behind `breakDown` and `live` at: https://arxiv.org/abs/1804.01955\n\nLooking for the `python` version of Break Down? Find it here: https://github.com/bondyra/pyBreakDown\n\n**New generation of the Break-Down algorithm is implemented in the iBreakDown package\nhttps://github.com/ModelOriented/iBreakDown**. All new features will be added to the iBreakDown.\n\n\n## Installation\n\nInstall from CRAN\n\n```\ninstall.packages(\"breakDown\")\n```\n\nInstall from GitHub\n\n```\ndevtools::install_github(\"pbiecek/breakDown\")\n```\n\n## Cheatsheets\n\n![Cheatsheet](https://raw.githubusercontent.com/pbiecek/breakDown/master/cheatsheets/breakDownCheatsheet.png)\n\n## Example for lm model\n\nGet data with [archivist](https://github.com/pbiecek/archivist)\n\n* broken object: `archivist::aread(\"pbiecek/breakDown/arepo/81c5be568d4db2ec795dedcb5d7d6599\")`\n* the plot: `archivist::aread(\"pbiecek/breakDown/arepo/7b40949a0fdf9c22780454581d4b556e\")`\n\nThe R code\n\n```{r}\nlibrary(breakDown)\nurl \u003c- 'https://archive.ics.uci.edu/ml/machine-learning-databases/wine-quality/winequality-white.csv'\nwine \u003c- read.table(url, header = T, sep=\";\")\nhead(wine, 3)\n##   fixed.acidity volatile.acidity citric.acid residual.sugar chlorides free.sulfur.dioxide total.sulfur.dioxide density   pH\n## 1           7.0             0.27        0.36           20.7     0.045                  45                  170  1.0010 3.00\n## 2           6.3             0.30        0.34            1.6     0.049                  14                  132  0.9940 3.30\n## 3           8.1             0.28        0.40            6.9     0.050                  30                   97  0.9951 3.26\n##   sulphates alcohol quality\n## 1      0.45     8.8       6\n## 2      0.49     9.5       6\n## 3      0.44    10.1       6\nmodel \u003c- lm(quality ~ fixed.acidity + volatile.acidity + citric.acid + residual.sugar + chlorides + free.sulfur.dioxide + total.sulfur.dioxide + density + pH + sulphates + alcohol,\n               data = wine)\nnew_observation \u003c- wine[1,]\nbr \u003c- broken(model, new_observation)\nbr\n##                            contribution\n## (Intercept)                     5.90000\n## residual.sugar = 20.7           1.20000\n## density = 1.001                -1.00000\n## alcohol = 8.8                  -0.33000\n## pH = 3                         -0.13000\n## free.sulfur.dioxide = 45        0.03600\n## sulphates = 0.45               -0.02500\n## volatile.acidity = 0.27         0.01500\n## fixed.acidity = 7               0.00950\n## total.sulfur.dioxide = 170     -0.00900\n## citric.acid = 0.36              0.00057\n## chlorides = 0.045               0.00019\n## final_prognosis                 5.60000\nplot(br)\n```\n![plot for lm model](misc/broken_lm.png)\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpbiecek%2Fbreakdown","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fpbiecek%2Fbreakdown","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpbiecek%2Fbreakdown/lists"}