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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++ 15.28% R 0.02% C 55.53% CSS 0.01% JavaScript 0.02% Jupyter Notebook 1.04% 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

Build Status |

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:

Tutorials

  • Tutorials are avaliable here.

For contributors

  • To contribute to CatBoost you need to first read CLA text and add to your pull request, that you agree to the terms of the CLA. More information can be found in CONTRIBUTING.md

  • Instructions for contributors can be found here.

Questions and bug reports

License

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

catboost's People

Contributors

exprmntr avatar climbsrocks avatar zamulla avatar bzz avatar alexey-milovidov avatar annaveronika avatar

Watchers

James Cloos avatar avatar

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