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
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 Query

Downloads:

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
macOS binaries:	r-release (arm64): xgb2sql_0.1.2.tgz, r-oldrel (arm64): xgb2sql_0.1.2.tgz, r-release (x86_64): xgb2sql_0.1.2.tgz, r-oldrel (x86_64): xgb2sql_0.1.2.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=xgb2sql to link to this page.