Hendrik/xgboost
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

[doc] Update the link to the tuning example in FLAML

Browse Source
This commit is contained in:
Qingyun Wu 2021-12-17 01:31:00 -05:00 committed by GitHub
parent 24e25802a7
commit b4a1236cfc
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
1 changed files with 1 additions and 1 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

2
demo/README.md
View File

@ -146,7 +146,7 @@ Send a PR to add a one sentence description:)
- [BayesBoost](https://github.com/mpearmain/BayesBoost) - Bayesian Optimization using xgboost and sklearn API
- [FLAML](https://github.com/microsoft/FLAML) - An open source AutoML library
designed to automatically produce accurate machine learning models with low computational cost. FLAML includes [XGBoost as one of the default learners](https://github.com/microsoft/FLAML/blob/main/flaml/model.py) and can also be used as a fast hyperparameter tuning tool for XGBoost ([code example](https://github.com/microsoft/FLAML/blob/main/notebook/flaml_xgboost.ipynb)).
designed to automatically produce accurate machine learning models with low computational cost. FLAML includes [XGBoost as one of the default learners](https://github.com/microsoft/FLAML/blob/main/flaml/model.py) and can also be used as a fast hyperparameter tuning tool for XGBoost ([code example](https://microsoft.github.io/FLAML/docs/Examples/AutoML-for-XGBoost)).
- [gp_xgboost_gridsearch](https://github.com/vatsan/gp_xgboost_gridsearch) - In-database parallel grid-search for XGBoost on [Greenplum](https://github.com/greenplum-db/gpdb) using PL/Python
- [tpot](https://github.com/rhiever/tpot) - A Python tool that automatically creates and optimizes machine learning pipelines using genetic programming.