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xgb2sql
View on CRAN: Click
here
Download and install xgb2sql package within the R console
Install from CRAN:
install.packages("xgb2sql")
Install from Github:
library("remotes")
install_github("cran/xgb2sql")
Install by package version:
library("remotes")
install_version("xgb2sql", "0.1.2")
Attach the package and use:
library("xgb2sql")
Maintained by
Chengjun Hou
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
10.32614/CRAN.package.xgb2sql . https://github.com/chengjunhou/xgb2sql/issues . https://github.com/chengjunhou/xgb2sql . xgb2sql results . xgb2sql.pdf . xgb2sql_0.1.2.tar.gz . xgb2sql_0.1.2.zip . xgb2sql_0.1.2.zip . xgb2sql_0.1.2.zip . xgb2sql_0.1.2.tgz . xgb2sql_0.1.2.tgz . xgb2sql_0.1.2.tgz . xgb2sql_0.1.2.tgz . xgb2sql_0.1.2.tgz . xgb2sql_0.1.2.tgz . https://CRAN.R-project.org/package=xgb2sql .
First Published: 2019-03-13
Latest Update: 2019-03-13
Description:
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>.
How to cite:
Chengjun Hou (2019). xgb2sql: Convert Trained 'XGBoost' Model to SQL Query. R package version 0.1.2, https://cran.r-project.org/web/packages/xgb2sql. Accessed 10 Apr. 2025.
Previous versions and publish date:
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Complete documentation for xgb2sql
Functions, R codes and Examples using
the xgb2sql R package
Some associated functions: booster2sql . onehot2sql .
Some associated R codes: booster2sql.R . onehot2sql.R . Full xgb2sql package functions and examples
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