{"Package":"Bodi","Title":"Boosting Diversity in Regression Ensembles","Version":"0.1.0","Authors@R":"c(\nperson(\"Yannig\", \"Goude\", email = \"yannig.goude@edf.fr\", role = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0003-2028-5536\")),\nperson(\"Mathias\", \"Bourel\", email = \"mbourel@fing.edu.uy\", role = c(\"aut\"),\ncomment = c(ORCID = \"0000-0002-7472-7179\")),\nperson(\"Jairo\", \"Cugliari\", email = \"jairo.cugliari@univ-lyon2.fr\", role = c(\"aut\"),\ncomment = c(ORCID = \"0000-0001-6779-0084\")),\nperson(\"Jean-Michel\", \"Poggi\", email = \"jean-michel.poggi@universite-paris-saclay.fr\", role = c(\"aut\"),\ncomment = c(ORCID = \"0000-0002-8222-1653\"))\n)","Description":"A gradient boosting-based algorithm by incorporating a diversity term to guide the gradient boosting iterations, see Bourel, Cugliari, Goude, Poggi (2021) .","License":"MIT + file LICENSE","Encoding":"UTF-8","Imports":"mgcv, ranger, rpart, gbm, opera","RoxygenNote":"7.1.2","NeedsCompilation":"no","Packaged":"2022-03-23 10:33:22 UTC; jairo","Maintainer":"Yannig Goude ","Author":"Yannig Goude [aut, cre] (),\nMathias Bourel [aut] (),\nJairo Cugliari [aut] (),\nJean-Michel Poggi [aut] ()","Repository":"CRAN","Date/Publication":"2022-03-23 12:40:02 UTC","repoType":"cran","tarballUrl":"ftp://cran.r-project.org/pub/R/src/contrib/Bodi_0.1.0.tar.gz","jsonAuthors":[{"name":"Yannig Goude","email":"yannig.goude@edf.fr","maintainer":true},{"name":"Mathias Bourel","email":"mbourel@fing.edu.uy","maintainer":false},{"name":"Jairo Cugliari","email":"jairo.cugliari@univ-lyon2.fr","maintainer":false},{"name":"Jean-Michel Poggi","email":"jean-michel.poggi@universite-paris-saclay.fr","maintainer":false}],"readme":"\n# Bodi\n\n\n\n\nThis R package \nimplements the [Bodi algorithm](https://hal.archives-ouvertes.fr/hal-03041309/).\nThe goal of Bodi (BOosting DIversity) is to construct a sequence of learners \nactively promoting diversity among them. Then, increasing diversity ensures the \nreduction of the mean-square-error producing a strong(er) ensemble learner. \n\n## Installation\n\nYou can install the released version of Bodi from [CRAN](https://CRAN.R-project.org) with (soon):\n\n``` r\ninstall.packages(\"Bodi\")\n```\n\nor from Gitlab (need to make repo public or use a PAT)\n\n``` r\nremotes::install_gitlab(\"yannig/bodi\")\n```\n\n## Example\n\nBodi has a main function called `boosting_diversity`. This basic example shows how to obtain the Bodi fit of a simple dataset :\n\n``` r\nlibrary(Bodi)\nall <- na.omit(airquality)\nsmp <- sample(nrow(all), .8 * nrow(all))\nboosting_diversity(\"Ozone\", \"Solar.R+Wind+Temp+Month+Day\", \n data0 = all[smp, ], data1 = all[-smp, ])\n```\n\nSee the documentation for further details.\n\n---\n\n## Acknowledgements\n\nThis research development benefited from the support of the «FMJH Research Initiative Data Science for Industry», and from the support to this program from EDF.","jobInfo":{"package":"Bodi","version":"0.1.0","parsingStatus":"success","parserVersion":1,"parsedAt":"2022-03-23T14:30:37+0000"}}

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