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CatBoost is an open-source gradient boosting on decision trees library with categorical features support out of the box for Python, R

License: Other

Python 23.39% Makefile 0.25% C++ 15.27% R 0.02% C 55.52% CSS 0.01% JavaScript 0.02% Jupyter Notebook 1.06% Protocol Buffer 0.11% Objective-C 0.24% CMake 0.01% Assembly 2.59% Shell 0.25% Java 0.88% Fortran 0.01% Batchfile 0.01% HTML 0.03% Roff 0.13% M4 0.04% TeX 0.19%

catboost's Introduction

Documentation | Installation

CatBoost is a machine learning method based on gradient boosting over decision trees.

Main advantages of CatBoost:

  • Superior quality when compared with other libraries.
  • Support for both numerical and categorical features.
  • Data visualization tools included.

The following implementations are available:

Questions and bug reports

License

© YANDEX LLC, 2017. Licensed under the Apache License, Version 2.0. See LICENSE file for more details.

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