xgb2sql: Convert Trained 'XGBoost' Model to SQL Query

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
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

Downloads:

Reference manual: xgb2sql.pdf
Vignettes: Deploy XGBoost Model as SQL Query
Package source: xgb2sql_0.1.2.tar.gz
Windows binaries: r-devel: xgb2sql_0.1.2.zip, r-release: xgb2sql_0.1.2.zip, r-oldrel: xgb2sql_0.1.2.zip
OS X binaries: r-release: xgb2sql_0.1.2.tgz, r-oldrel: not available

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