catboost/catboost

A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

PythonCC++AssemblyCythonFortranOtherpythondata-sciencemachine-learningdata-miningtutorialrbig-datagpucudakagglegbdtgbmgpu-computingdecision-treesgradient-boostingcoremlcatboostcategorical-features
This is stars and forks stats for /catboost/catboost repository. As of 28 Apr, 2024 this repository has 7387 stars and 1146 forks.

Website | Documentation | Tutorials | Installation | Release Notes CatBoost is a machine learning method based on gradient boosting over decision trees. Main advantages of CatBoost: Superior quality when compared with other GBDT libraries on many datasets. Best in class prediction speed. Support for both numerical and categorical features. Fast GPU and multi-GPU support for training out of the box. Visualization tools included. Fast and reproducible distributed training with Apache Spark and CLI. Get...
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