Package: xgb2sql 0.1.2
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://github.com/dmlc/xgboost> 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>.
Authors:
xgb2sql_0.1.2.tar.gz
xgb2sql_0.1.2.zip(r-4.5)xgb2sql_0.1.2.zip(r-4.4)xgb2sql_0.1.2.zip(r-4.3)
xgb2sql_0.1.2.tgz(r-4.4-any)xgb2sql_0.1.2.tgz(r-4.3-any)
xgb2sql_0.1.2.tar.gz(r-4.5-noble)xgb2sql_0.1.2.tar.gz(r-4.4-noble)
xgb2sql_0.1.2.tgz(r-4.4-emscripten)xgb2sql_0.1.2.tgz(r-4.3-emscripten)
xgb2sql.pdf |xgb2sql.html✨
xgb2sql/json (API)
NEWS
# Install 'xgb2sql' in R: |
install.packages('xgb2sql', repos = c('https://chengjunhou.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/chengjunhou/xgb2sql/issues
Last updated 3 years agofrom:b2c9e9dc96. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 30 2024 |
R-4.5-win | OK | Oct 30 2024 |
R-4.5-linux | OK | Oct 30 2024 |
R-4.4-win | OK | Oct 30 2024 |
R-4.4-mac | OK | Oct 30 2024 |
R-4.3-win | OK | Oct 30 2024 |
R-4.3-mac | OK | Oct 30 2024 |
Exports:booster2sqlonehot2sql
Dependencies:data.tablejsonlitelatticeMatrixxgboost