mcboost

mcboost: Multi-Calibration Boosting for R - Published in JOSS (2021)

Science Score: 95.0%

This score indicates how likely this project is to be science-related based on various indicators:

○
CITATION.cff file
✓
codemeta.json file
Found codemeta.json file
✓
.zenodo.json file
Found .zenodo.json file
✓
DOI references
Found 10 DOI reference(s) in README and JOSS metadata
✓
Academic publication links
Links to: arxiv.org, joss.theoj.org
✓
Committers with academic emails
1 of 8 committers (12.5%) from academic institutions
○
Institutional organization owner
✓
JOSS paper metadata
Published in Journal of Open Source Software

Keywords

bias-correction bias-detection classification ethics fairness fairness-ai fairness-ml machine-learning post-processing responsible-ai

Last synced: 4 months ago · JSON representation

Repository

Multi-Calibration & Multi-Accuracy Boosting for R

Basic Info

Host: GitHub
Owner: mlr-org
License: other
Language: R
Default Branch: main
Homepage:
Size: 864 KB

Statistics

Stars: 32
Watchers: 4
Forks: 4
Open Issues: 6
Releases: 6

Topics

bias-correction bias-detection classification ethics fairness fairness-ai fairness-ml machine-learning post-processing responsible-ai

Created almost 5 years ago · Last pushed 5 months ago

Metadata Files

Readme Changelog License Code of conduct Codemeta

mcboost

What does it do?

mcboost implements Multi-Calibration Boosting (Hebert-Johnson et al., 2018; Kim et al., 2019) for the multi-calibration of a machine learning model's prediction. Multi-Calibration works best in scenarios where the underlying data & labels are unbiased but a bias is introduced within the algorithm's fitting procedure. This is often the case, e.g. when an algorithm fits a majority population while ignoring or under-fitting minority populations.

For more information and example, see the package's website.

More details with respect to usage and the procedures can be found in the package vignettes.

Installation

The current version can be downloaded from CRAN using:

r install.packages("mcboost")

You can install the development version of mcboost from Github with:

r remotes::install_github("mlr-org/mcboost")

Usage

Post-processing with mcboost needs three components. We start with an initial prediction model (1) and an auditing algorithm (2) that may be customized by the user. The auditing algorithm then runs Multi-Calibration-Boosting on a labeled auditing dataset (3). The resulting model can be used for obtaining multi-calibrated predictions.

Example

In this simple example, our goal is to improve calibration for an initial predictor, e.g. a ML algorithm trained on an initial task. Internally, mcboost often makes use of mlr3 and learners that come with mlr3learners.

r library(mcboost) library(mlr3)

First we set up an example dataset.

r # Example Data: Sonar Task tsk = tsk("sonar") tid = sample(tsk$row_ids, 100) # 100 rows for training train_data = tsk$data(cols = tsk$feature_names, rows = tid) train_labels = tsk$data(cols = tsk$target_names, rows = tid)[[1]]

To provide an example, we assume that we have already a learner l which we train below. We can now wrap this initial learner's predict function for use with mcboost, since mcboost expects the initial model to be specified as a function with data as input.

```r l = lrn("classif.rpart") l$train(tsk$clone()$filter(tid))

initpredictor = function(data) { # Get response prediction from Learner p = l$predictnewdata(data)$response # One-hot encode and take first column one_hot(p) } ```

We can now run Multi-Calibration Boosting by instantiating the object and calling the multicalibrate method. Note, that typically, we would use Multi-Calibration on a separate validation set! We furthermore select the auditor model, a SubpopAuditorFitter, in our case a Decision Tree:

r mc = MCBoost$new( init_predictor = init_predictor, auditor_fitter = "TreeAuditorFitter") mc$multicalibrate(train_data, train_labels)

Lastly, we predict on new data.

r tstid = setdiff(tsk$row_ids, tid) # held-out data test_data = tsk$data(cols = tsk$feature_names, rows = tstid) mc$predict_probs(test_data)

Multi-Calibration

While mcboost in its defaults implements Multi-Accuracy (Kim et al., 2019), it can also multi-calibrate predictors (Hebert-Johnson et al., 2018). In order to achieve this, we have to set the following hyperparameters:

r mc = MCBoost$new( init_predictor = init_predictor, auditor_fitter = "TreeAuditorFitter", num_buckets = 10, multiplicative = FALSE )

MCBoost as a PipeOp

mcboost can also be used within a mlr3pipeline in order to use at the full end-to-end pipeline (in the form of a GraphLearner).

r library(mlr3) library(mlr3pipelines) gr = ppl_mcboost(lrn("classif.rpart")) tsk = tsk("sonar") tid = sample(1:208, 108) gr$train(tsk$clone()$filter(tid)) gr$predict(tsk$clone()$filter(setdiff(1:208, tid)))

Further Examples

The mcboost vignettes Basics and Extensions and Health Survey Example demonstrate a lot of interesting showcases for applying mcboost.

Contributing

This R package is licensed under the LGPL-3. If you encounter problems using this software (lack of documentation, misleading or wrong documentation, unexpected behaviour, bugs, …) or just want to suggest features, please open an issue in the issue tracker. Pull requests are welcome and will be included at the discretion of the maintainers.

As this project is developed with mlr3's style guide in mind, the following resources can be helpful to individuals wishing to contribute: Please consult the wiki for a style guide, a roxygen guide and a pull request guide.

Code of Conduct

Please note that the mcboost project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.

Citing mcboost

If you use mcboost, please cite our package as well as the two papers it is based on:

@article{pfisterer2021, author = {Pfisterer, Florian and Kern, Christoph and Dandl, Susanne and Sun, Matthew and Kim, Michael P. and Bischl, Bernd}, title = {mcboost: Multi-Calibration Boosting for R}, journal = {Journal of Open Source Software}, doi = {10.21105/joss.03453}, url = {https://doi.org/10.21105/joss.03453}, year = {2021}, publisher = {The Open Journal}, volume = {6}, number = {64}, pages = {3453} } # Multi-Calibration @inproceedings{hebert-johnson2018, title = {Multicalibration: Calibration for the ({C}omputationally-Identifiable) Masses}, author = {Hebert-Johnson, Ursula and Kim, Michael P. and Reingold, Omer and Rothblum, Guy}, booktitle = {Proceedings of the 35th International Conference on Machine Learning}, pages = {1939--1948}, year = {2018}, editor = {Jennifer Dy and Andreas Krause}, volume = {80}, series = {Proceedings of Machine Learning Research}, address = {Stockholmsmässan, Stockholm Sweden}, publisher = {PMLR} } # Multi-Accuracy @inproceedings{kim2019, author = {Kim, Michael P. and Ghorbani, Amirata and Zou, James}, title = {Multiaccuracy: Black-Box Post-Processing for Fairness in Classification}, year = {2019}, isbn = {9781450363242}, publisher = {Association for Computing Machinery}, address = {New York, NY, USA}, url = {https://doi.org/10.1145/3306618.3314287}, doi = {10.1145/3306618.3314287}, booktitle = {Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society}, pages = {247--254}, location = {Honolulu, HI, USA}, series = {AIES '19} }

Owner

Name: mlr-org
Login: mlr-org
Kind: organization
Location: Munich, Germany

Website: https://mlr-org.com
Repositories: 80
Profile: https://github.com/mlr-org

JOSS Publication

mcboost: Multi-Calibration Boosting for R

Published

August 06, 2021

DOI

10.21105/joss.03453

Volume 6, Issue 64, Page 3453

Authors

Florian Pfisterer

Ludwig Maximilian University of Munich

Christoph Kern

University of Mannheim

Susanne Dandl

Ludwig Maximilian University of Munich

Matthew Sun
Princeton University

Michael P. Kim
UC Berkeley

Bernd Bischl

Ludwig Maximilian University of Munich

Editor

Øystein Sørensen

CodeMeta (codemeta.json)

{
  "@context": "https://doi.org/10.5063/schema/codemeta-2.0",
  "@type": "SoftwareSourceCode",
  "identifier": "mcboost",
  "description": "Implements 'Multi-Calibration Boosting' (2018) <https://proceedings.mlr.press/v80/hebert-johnson18a.html> and 'Multi-Accuracy Boosting' (2019) <arXiv:1805.12317> for the multi-calibration of a machine learning model's prediction. 'MCBoost' updates predictions for sub-groups in an iterative fashion in order to mitigate biases like poor calibration or large accuracy differences across subgroups. Multi-Calibration works best in scenarios where the underlying data & labels are unbiased, but resulting models are. This is often the case, e.g. when an algorithm fits a majority population while ignoring or under-fitting minority populations.",
  "name": "mcboost: Multi-Calibration Boosting",
  "codeRepository": "https://github.com/mlr-org/mcboost",
  "issueTracker": "https://github.com/mlr-org/mcboost/issues",
  "license": "https://spdx.org/licenses/LGPL-3.0",
  "version": "0.4.0",
  "programmingLanguage": {
    "@type": "ComputerLanguage",
    "name": "R",
    "url": "https://r-project.org"
  },
  "runtimePlatform": "R version 4.1.2 (2021-11-01)",
  "provider": {
    "@id": "https://cran.r-project.org",
    "@type": "Organization",
    "name": "Comprehensive R Archive Network (CRAN)",
    "url": "https://cran.r-project.org"
  },
  "author": [
    {
      "@type": "Person",
      "givenName": "Florian",
      "familyName": "Pfisterer",
      "email": "pfistererf@googlemail.com",
      "@id": "https://orcid.org/0000-0001-8867-762X"
    }
  ],
  "contributor": [
    {
      "@type": "Person",
      "givenName": "Susanne",
      "familyName": "Dandl",
      "email": "susanne.dandl@stat.uni-muenchen.de",
      "@id": "https://orcid.org/0000-0003-4324-4163"
    },
    {
      "@type": "Person",
      "givenName": "Christoph",
      "familyName": "Kern",
      "email": "c.kern@uni-mannheim.de",
      "@id": "https://orcid.org/0000-0001-7363-4299"
    },
    {
      "@type": "Person",
      "givenName": "Carolin",
      "familyName": "Becker"
    },
    {
      "@type": "Person",
      "givenName": "Bernd",
      "familyName": "Bischl",
      "email": "bernd_bischl@gmx.net",
      "@id": "https://orcid.org/0000-0001-6002-6980"
    }
  ],
  "maintainer": [
    {
      "@type": "Person",
      "givenName": "Florian",
      "familyName": "Pfisterer",
      "email": "pfistererf@googlemail.com",
      "@id": "https://orcid.org/0000-0001-8867-762X"
    }
  ],
  "softwareSuggestions": [
    {
      "@type": "SoftwareApplication",
      "identifier": "curl",
      "name": "curl",
      "provider": {
        "@id": "https://cran.r-project.org",
        "@type": "Organization",
        "name": "Comprehensive R Archive Network (CRAN)",
        "url": "https://cran.r-project.org"
      },
      "sameAs": "https://CRAN.R-project.org/package=curl"
    },
    {
      "@type": "SoftwareApplication",
      "identifier": "lgr",
      "name": "lgr",
      "provider": {
        "@id": "https://cran.r-project.org",
        "@type": "Organization",
        "name": "Comprehensive R Archive Network (CRAN)",
        "url": "https://cran.r-project.org"
      },
      "sameAs": "https://CRAN.R-project.org/package=lgr"
    },
    {
      "@type": "SoftwareApplication",
      "identifier": "formattable",
      "name": "formattable",
      "provider": {
        "@id": "https://cran.r-project.org",
        "@type": "Organization",
        "name": "Comprehensive R Archive Network (CRAN)",
        "url": "https://cran.r-project.org"
      },
      "sameAs": "https://CRAN.R-project.org/package=formattable"
    },
    {
      "@type": "SoftwareApplication",
      "identifier": "tidyverse",
      "name": "tidyverse",
      "provider": {
        "@id": "https://cran.r-project.org",
        "@type": "Organization",
        "name": "Comprehensive R Archive Network (CRAN)",
        "url": "https://cran.r-project.org"
      },
      "sameAs": "https://CRAN.R-project.org/package=tidyverse"
    },
    {
      "@type": "SoftwareApplication",
      "identifier": "PracTools",
      "name": "PracTools",
      "provider": {
        "@id": "https://cran.r-project.org",
        "@type": "Organization",
        "name": "Comprehensive R Archive Network (CRAN)",
        "url": "https://cran.r-project.org"
      },
      "sameAs": "https://CRAN.R-project.org/package=PracTools"
    },
    {
      "@type": "SoftwareApplication",
      "identifier": "mlr3learners",
      "name": "mlr3learners",
      "provider": {
        "@id": "https://cran.r-project.org",
        "@type": "Organization",
        "name": "Comprehensive R Archive Network (CRAN)",
        "url": "https://cran.r-project.org"
      },
      "sameAs": "https://CRAN.R-project.org/package=mlr3learners"
    },
    {
      "@type": "SoftwareApplication",
      "identifier": "mlr3oml",
      "name": "mlr3oml",
      "provider": {
        "@id": "https://cran.r-project.org",
        "@type": "Organization",
        "name": "Comprehensive R Archive Network (CRAN)",
        "url": "https://cran.r-project.org"
      },
      "sameAs": "https://CRAN.R-project.org/package=mlr3oml"
    },
    {
      "@type": "SoftwareApplication",
      "identifier": "neuralnet",
      "name": "neuralnet",
      "provider": {
        "@id": "https://cran.r-project.org",
        "@type": "Organization",
        "name": "Comprehensive R Archive Network (CRAN)",
        "url": "https://cran.r-project.org"
      },
      "sameAs": "https://CRAN.R-project.org/package=neuralnet"
    },
    {
      "@type": "SoftwareApplication",
      "identifier": "paradox",
      "name": "paradox",
      "provider": {
        "@id": "https://cran.r-project.org",
        "@type": "Organization",
        "name": "Comprehensive R Archive Network (CRAN)",
        "url": "https://cran.r-project.org"
      },
      "sameAs": "https://CRAN.R-project.org/package=paradox"
    },
    {
      "@type": "SoftwareApplication",
      "identifier": "testthat",
      "name": "testthat",
      "provider": {
        "@id": "https://cran.r-project.org",
        "@type": "Organization",
        "name": "Comprehensive R Archive Network (CRAN)",
        "url": "https://cran.r-project.org"
      },
      "sameAs": "https://CRAN.R-project.org/package=testthat"
    },
    {
      "@type": "SoftwareApplication",
      "identifier": "knitr",
      "name": "knitr",
      "provider": {
        "@id": "https://cran.r-project.org",
        "@type": "Organization",
        "name": "Comprehensive R Archive Network (CRAN)",
        "url": "https://cran.r-project.org"
      },
      "sameAs": "https://CRAN.R-project.org/package=knitr"
    },
    {
      "@type": "SoftwareApplication",
      "identifier": "ranger",
      "name": "ranger",
      "provider": {
        "@id": "https://cran.r-project.org",
        "@type": "Organization",
        "name": "Comprehensive R Archive Network (CRAN)",
        "url": "https://cran.r-project.org"
      },
      "sameAs": "https://CRAN.R-project.org/package=ranger"
    },
    {
      "@type": "SoftwareApplication",
      "identifier": "rmarkdown",
      "name": "rmarkdown",
      "provider": {
        "@id": "https://cran.r-project.org",
        "@type": "Organization",
        "name": "Comprehensive R Archive Network (CRAN)",
        "url": "https://cran.r-project.org"
      },
      "sameAs": "https://CRAN.R-project.org/package=rmarkdown"
    },
    {
      "@type": "SoftwareApplication",
      "identifier": "survival",
      "name": "survival",
      "provider": {
        "@id": "https://cran.r-project.org",
        "@type": "Organization",
        "name": "Comprehensive R Archive Network (CRAN)",
        "url": "https://cran.r-project.org"
      },
      "sameAs": "https://CRAN.R-project.org/package=survival"
    },
    {
      "@type": "SoftwareApplication",
      "identifier": "xgboost",
      "name": "xgboost",
      "provider": {
        "@id": "https://cran.r-project.org",
        "@type": "Organization",
        "name": "Comprehensive R Archive Network (CRAN)",
        "url": "https://cran.r-project.org"
      },
      "sameAs": "https://CRAN.R-project.org/package=xgboost"
    },
    {
      "@type": "SoftwareApplication",
      "identifier": "covr",
      "name": "covr",
      "provider": {
        "@id": "https://cran.r-project.org",
        "@type": "Organization",
        "name": "Comprehensive R Archive Network (CRAN)",
        "url": "https://cran.r-project.org"
      },
      "sameAs": "https://CRAN.R-project.org/package=covr"
    }
  ],
  "softwareRequirements": {
    "1": {
      "@type": "SoftwareApplication",
      "identifier": "R",
      "name": "R",
      "version": ">= 3.1.0"
    },
    "2": {
      "@type": "SoftwareApplication",
      "identifier": "backports",
      "name": "backports",
      "provider": {
        "@id": "https://cran.r-project.org",
        "@type": "Organization",
        "name": "Comprehensive R Archive Network (CRAN)",
        "url": "https://cran.r-project.org"
      },
      "sameAs": "https://CRAN.R-project.org/package=backports"
    },
    "3": {
      "@type": "SoftwareApplication",
      "identifier": "checkmate",
      "name": "checkmate",
      "version": ">= 2.0.0",
      "provider": {
        "@id": "https://cran.r-project.org",
        "@type": "Organization",
        "name": "Comprehensive R Archive Network (CRAN)",
        "url": "https://cran.r-project.org"
      },
      "sameAs": "https://CRAN.R-project.org/package=checkmate"
    },
    "4": {
      "@type": "SoftwareApplication",
      "identifier": "data.table",
      "name": "data.table",
      "version": ">= 1.13.6",
      "provider": {
        "@id": "https://cran.r-project.org",
        "@type": "Organization",
        "name": "Comprehensive R Archive Network (CRAN)",
        "url": "https://cran.r-project.org"
      },
      "sameAs": "https://CRAN.R-project.org/package=data.table"
    },
    "5": {
      "@type": "SoftwareApplication",
      "identifier": "mlr3",
      "name": "mlr3",
      "version": ">= 0.10",
      "provider": {
        "@id": "https://cran.r-project.org",
        "@type": "Organization",
        "name": "Comprehensive R Archive Network (CRAN)",
        "url": "https://cran.r-project.org"
      },
      "sameAs": "https://CRAN.R-project.org/package=mlr3"
    },
    "6": {
      "@type": "SoftwareApplication",
      "identifier": "mlr3misc",
      "name": "mlr3misc",
      "version": ">= 0.8.0",
      "provider": {
        "@id": "https://cran.r-project.org",
        "@type": "Organization",
        "name": "Comprehensive R Archive Network (CRAN)",
        "url": "https://cran.r-project.org"
      },
      "sameAs": "https://CRAN.R-project.org/package=mlr3misc"
    },
    "7": {
      "@type": "SoftwareApplication",
      "identifier": "mlr3pipelines",
      "name": "mlr3pipelines",
      "version": ">= 0.3.0",
      "provider": {
        "@id": "https://cran.r-project.org",
        "@type": "Organization",
        "name": "Comprehensive R Archive Network (CRAN)",
        "url": "https://cran.r-project.org"
      },
      "sameAs": "https://CRAN.R-project.org/package=mlr3pipelines"
    },
    "8": {
      "@type": "SoftwareApplication",
      "identifier": "mlr3proba",
      "name": "mlr3proba",
      "version": ">= 0.4.0",
      "provider": {
        "@id": "https://cran.r-project.org",
        "@type": "Organization",
        "name": "Comprehensive R Archive Network (CRAN)",
        "url": "https://cran.r-project.org"
      },
      "sameAs": "https://CRAN.R-project.org/package=mlr3proba"
    },
    "9": {
      "@type": "SoftwareApplication",
      "identifier": "R6",
      "name": "R6",
      "version": ">= 2.4.1",
      "provider": {
        "@id": "https://cran.r-project.org",
        "@type": "Organization",
        "name": "Comprehensive R Archive Network (CRAN)",
        "url": "https://cran.r-project.org"
      },
      "sameAs": "https://CRAN.R-project.org/package=R6"
    },
    "10": {
      "@type": "SoftwareApplication",
      "identifier": "rpart",
      "name": "rpart",
      "provider": {
        "@id": "https://cran.r-project.org",
        "@type": "Organization",
        "name": "Comprehensive R Archive Network (CRAN)",
        "url": "https://cran.r-project.org"
      },
      "sameAs": "https://CRAN.R-project.org/package=rpart"
    },
    "11": {
      "@type": "SoftwareApplication",
      "identifier": "glmnet",
      "name": "glmnet",
      "provider": {
        "@id": "https://cran.r-project.org",
        "@type": "Organization",
        "name": "Comprehensive R Archive Network (CRAN)",
        "url": "https://cran.r-project.org"
      },
      "sameAs": "https://CRAN.R-project.org/package=glmnet"
    },
    "SystemRequirements": null
  },
  "fileSize": "272.663KB",
  "citation": [
    {
      "@type": "ScholarlyArticle",
      "datePublished": "2021",
      "author": [
        {
          "@type": "Person",
          "givenName": "Florian",
          "familyName": "Pfisterer"
        },
        {
          "@type": "Person",
          "givenName": "Christoph",
          "familyName": "Kern"
        },
        {
          "@type": "Person",
          "givenName": "Susanne",
          "familyName": "Dandl"
        },
        {
          "@type": "Person",
          "givenName": "Matthew",
          "familyName": "Sun"
        },
        {
          "@type": "Person",
          "givenName": "Michael P.",
          "familyName": "Kim"
        },
        {
          "@type": "Person",
          "givenName": "Bernd",
          "familyName": "Bischl"
        }
      ],
      "name": "mcboost: Multi-Calibration Boosting for R",
      "identifier": "10.21105/joss.03453",
      "url": "https://joss.theoj.org/papers/10.21105/joss.03453",
      "pagination": "3453",
      "@id": "https://doi.org/10.21105/joss.03453",
      "sameAs": "https://doi.org/10.21105/joss.03453",
      "isPartOf": {
        "@type": "PublicationIssue",
        "issueNumber": "64",
        "datePublished": "2021",
        "isPartOf": {
          "@type": [
            "PublicationVolume",
            "Periodical"
          ],
          "volumeNumber": "6",
          "name": "Journal of Open Source Software"
        }
      }
    }
  ],
  "releaseNotes": "https://github.com/mlr-org/mcboost/blob/master/NEWS.md",
  "readme": "https://github.com/mlr-org/mcboost/blob/main/README.md",
  "contIntegration": "https://github.com/mlr-org/mcboost/actions",
  "developmentStatus": "https://lifecycle.r-lib.org/articles/stages.html#experimental",
  "keywords": [
    "machine-learning",
    "classification",
    "fairness",
    "fairness-ml",
    "fairness-ai",
    "responsible-ai",
    "bias-correction",
    "bias-detection",
    "post-processing",
    "ethics"
  ],
  "relatedLink": "https://CRAN.R-project.org/package=mcboost"
}

GitHub Events

Total

Issues event: 1
Watch event: 2
Issue comment event: 2
Push event: 1
Create event: 1

Last Year

Issues event: 1
Watch event: 2
Issue comment event: 2
Push event: 1
Create event: 1

Committers

Last synced: 5 months ago

All Time

Total Commits: 298
Total Committers: 8
Avg Commits per committer: 37.25
Development Distribution Score (DDS): 0.48

Past Year

Commits: 3
Committers: 1
Avg Commits per committer: 3.0
Development Distribution Score (DDS): 0.0

Top Committers

Name	Email	Commits
pfistfl	p**f@g**m	155
Carolin	c**r@c**e	56
chkern	c**n@u**e	50
susanne-207	d**e@g**m	27
Sebastian Fischer	s**r@g**m	5
mikekimbackward	m**d@g**m	3
Owen Ward	3****d	1
Matthew Sun	m**8@g**m	1

Committer Domains (Top 20 + Academic)

uni-mannheim.de: 1 campus.lmu.de: 1

Issues and Pull Requests

Last synced: 4 months ago

All Time

Total issues: 38
Total pull requests: 8
Average time to close issues: 12 days
Average time to close pull requests: about 2 months
Total issue authors: 7
Total pull request authors: 6
Average comments per issue: 1.0
Average comments per pull request: 0.5
Merged pull requests: 7
Bot issues: 0
Bot pull requests: 0

Past Year

Issues: 2
Pull requests: 0
Average time to close issues: N/A
Average time to close pull requests: N/A
Issue authors: 2
Pull request authors: 0
Average comments per issue: 1.0
Average comments per pull request: 0
Merged pull requests: 0
Bot issues: 0
Bot pull requests: 0

View more stats

Top Authors

Issue Authors

pfistfl (29)
chkern (3)
dandls (2)
flinder (1)
be-marc (1)
carobec (1)
unai-fa (1)

Pull Request Authors

mb706 (2)
sebffischer (2)
dandls (2)
carobec (2)
OwenWard (1)
chkern (1)

Top Labels

Issue Labels

enhancement (1)

Pull Request Labels

enhancement (1)

Packages

Total packages: 1
Total downloads:
- cran 328 last-month

Total dependent packages: 0
Total dependent repositories: 0
Total versions: 7
Total maintainers: 1

cran.r-project.org: mcboost

Multi-Calibration Boosting

Homepage: https://github.com/mlr-org/mcboost
Documentation: http://cran.r-project.org/web/packages/mcboost/mcboost.pdf
License: LGPL (≥ 3)
Latest release: 0.4.4
published 5 months ago

Versions: 7
Dependent Packages: 0
Dependent Repositories: 0
Downloads: 328 Last month

Rankings

Stargazers count: 10.7%

Forks count: 12.8%

Average: 26.2%

Dependent packages count: 29.8%

Dependent repos count: 35.5%

Downloads: 42.1%

Maintainers (1)

sebf.fischer@gmail.com

Last synced: 4 months ago

Dependencies

DESCRIPTION cran

R >= 3.1.0 depends
R6 >= 2.4.1 imports
backports * imports
checkmate >= 2.0.0 imports
data.table >= 1.13.6 imports
glmnet * imports
mlr3 >= 0.10 imports
mlr3misc >= 0.8.0 imports
mlr3pipelines >= 0.3.0 imports
rmarkdown * imports
rpart * imports
PracTools * suggests
covr * suggests
curl * suggests
formattable * suggests
knitr * suggests
lgr * suggests
mlr3learners * suggests
mlr3oml * suggests
neuralnet * suggests
paradox * suggests
ranger * suggests
testthat >= 3.1.0 suggests
tidyverse * suggests
xgboost * suggests

.github/workflows/tic.yml actions

actions/checkout v2.3.4 composite
actions/upload-artifact v2.2.1 composite
pat-s/always-upload-cache v2.1.3 composite
r-lib/actions/setup-pandoc master composite
r-lib/actions/setup-r master composite
r-lib/actions/setup-tinytex master composite

mcboost

Science Score: 95.0%

Keywords

Repository

Basic Info

Statistics

Topics

Metadata Files

README.md

mcboost

What does it do?

Installation

Usage

Example

Multi-Calibration

MCBoost as a PipeOp

Further Examples

Contributing

Code of Conduct

Citing mcboost

Owner

JOSS Publication

mcboost: Multi-Calibration Boosting for R

Authors

Editor

Tags

CodeMeta (codemeta.json)

GitHub Events

Total

Last Year

Committers

All Time

Past Year

Top Committers

Committer Domains (Top 20 + Academic)

Issues and Pull Requests

All Time

Past Year

Top Authors

Issue Authors

Pull Request Authors

Top Labels

Issue Labels

Pull Request Labels

Packages

cran.r-project.org: mcboost

Rankings

Maintainers (1)

Dependencies