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General purpose gradient boosting on decision trees library with categorical features support out of the box. It is easy to install, contains fast inference implementation and supports CPU and GPU (even multi-GPU) computation.

Uploaded Mon Mar 31 20:58:48 2025
md5 checksum ab7ce0a95ef4872aee829c488c5bfdd2
arch x86_64
build py311h06a4308_0
depends matplotlib-base, numpy >=1.16.0,<2.0a0, pandas >=0.24.0, plotly, python >=3.11,<3.12.0a0, python-graphviz, scipy, six
license Apache-2.0
license_family Apache
md5 ab7ce0a95ef4872aee829c488c5bfdd2
name catboost
platform linux
sha1 2c216fe5c1d9d61af70260da4ef279c5e2ee205d
sha256 6a94d7c6532dd5a7eddc66406d1da8a852e0068d9a5febbc024d02bd2b657d6d
size 54412455
subdir linux-64
timestamp 1685039991562
version 1.2