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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 20:58:46 2025
md5 checksum 6531c19ede3600804dbd18f00147718b
arch x86_64
build py310h06a4308_0
depends matplotlib-base, numpy >=1.16.0,<2.0a0, pandas >=0.24.0, plotly, python >=3.10,<3.11.0a0, python-graphviz, scipy, six
license Apache-2.0
license_family Apache
md5 6531c19ede3600804dbd18f00147718b
name catboost
platform linux
sha1 2f0bbea9d63f05706f7a4ec39d0aeb31d29d6bc2
sha256 1afbbd36f0fccb0f6a5e92aa4f07586aafaca91ff4dba743fb3768b42e35428f
size 54351336
subdir linux-64
timestamp 1685039853387
version 1.2