This tool enables in-database scoring of 'XGBoost' models built in R, by translating trained model objects into SQL query. 'XGBoost' <https://xgboost.readthedocs.io/en/latest/index.html> provides parallel tree boosting (also known as gradient boosting machine, or GBM) algorithms in a highly efficient, flexible and portable way. GBM algorithm is introduced by Friedman (2001) <doi:10.1214/aos/1013203451>, and more details on 'XGBoost' can be found in Chen & Guestrin (2016) <doi:10.1145/2939672.2939785>.
Version: 0.1.2 Depends: R (≥ 3.1.0) Imports: xgboost (≥ 0.81.0.1), data.table (≥ 1.12.0) Suggests: ggplot2, knitr, rmarkdown Published: 2019-03-13 DOI: 10.32614/CRAN.package.xgb2sql Author: Chengjun Hou [aut, cre], Abhishek Bishoyi [aut] Maintainer: Chengjun Hou <chengjun.hou at gmail.com> BugReports: https://github.com/chengjunhou/xgb2sql/issues License: MIT + file LICENSE URL: https://github.com/chengjunhou/xgb2sql NeedsCompilation: no CRAN checks: xgb2sql results Documentation: Reference manual: xgb2sql.pdf Vignettes: Deploy XGBoost Model as SQL QueryPlease use the canonical form https://CRAN.R-project.org/package=xgb2sql to link to this page.
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