Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
-
Updated
Jul 3, 2024 - C++
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
Deep Learning API and Server in C++14 support for Caffe, PyTorch,TensorRT, Dlib, NCNN, Tensorflow, XGBoost and TSNE
Real time eye tracking for embedded and mobile devices.
Secure collaborative training and inference for XGBoost.
[ICML 2019, 20 min long talk] Robust Decision Trees Against Adversarial Examples
[NeurIPS 2019] H. Chen*, H. Zhang*, S. Si, Y. Li, D. Boning and C.-J. Hsieh, Robustness Verification of Tree-based Models (*equal contribution)
Simple C++ interface for XGBoost(binary classification)
This project implements a common rest server which can serve tensorflow-serving & xgboost models.
Auto-ML based on a coevolutionary model.
Machine Learning Models Deployment using C++ Code Generation
A simple stand-alone version of XGBoost named EasyXGB.
Predict the cost of a CMAPD assignment with XGBoost regression
Muse Demographic Membership Top Coder Data Science Marathon Match
Easy xgboost installation for R users (no recursive)
counterfactual explanations for XGBoost and tree ensemble models - counterfactual reasoning - model interpretability
Electronic Parts Classification Top Coder Data Science Marathon Match
Add a description, image, and links to the xgboost topic page so that developers can more easily learn about it.
To associate your repository with the xgboost topic, visit your repo's landing page and select "manage topics."