Xgb
XGBoost - the high performance machine learning library - for Ruby
:fire: Uses the C API for blazing performance
Installation
First, install XGBoost. On Mac, copy lib/libxgboost.dylib
to /usr/local/lib
.
Add this line to your application’s Gemfile:
gem 'xgb'
Getting Started
Train a model
params = {objective: "reg:squarederror"}
train_set = Xgb::DMatrix.new(x_train, label: y_train)
booster = Xgb.train(params, train_set)
Predict
booster.predict(x_test)
Save the model to a file
booster.save_model("model.txt")
Load the model from a file
booster = Xgb::Booster.new(model_file: "model.txt")
Reference
This library follows the Core Data Structure and Learning APIs for the Python library. Some methods and options are missing at the moment. PRs welcome!
Helpful Resources
Related Projects
Credits
Thanks to the xgboost gem for serving as an initial reference, and Selva Prabhakaran for the test datasets.
History
View the changelog
Contributing
Everyone is encouraged to help improve this project. Here are a few ways you can help:
- Report bugs
- Fix bugs and submit pull requests
- Write, clarify, or fix documentation
- Suggest or add new features