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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 20:58:38 2025
md5 checksum 991b4cd1d7b0d811575d73d00e85ad07
arch x86_64
build py310h06a4308_0
constrains ipywidgets >=7.0,<9.0
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 991b4cd1d7b0d811575d73d00e85ad07
name catboost
platform linux
sha1 8dfc1ff9b6b071b529783471b925724c410f8788
sha256 45b0129a5c73b9e713f8501fdb47ea73a64ed82580f1deb7a531d1905fd87744
size 54200195
subdir linux-64
timestamp 1711453944682
version 1.2.3