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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 20:58:41 2025
md5 checksum 15966e56d5990f11e1e73837d60e82f4
arch x86_64
build py311h06a4308_0
constrains ipywidgets >=7.0,<9.0
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 15966e56d5990f11e1e73837d60e82f4
name catboost
platform linux
sha1 d5d4b15f4aa6a38a328dc5281f67d67d6e8f85d6
sha256 d02cf6555b1f8c38c3521c3ace8c37d9fbcff4808f242f36f0c2b99e48f4f24c
size 54242695
subdir linux-64
timestamp 1711454192335
version 1.2.3