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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 20:58:43 2025
md5 checksum 457c306a5aac68d885e490c5f3d3fc65
arch x86_64
build py312h06a4308_0
constrains ipywidgets >=7.0,<9.0
depends matplotlib-base, numpy >=1.16.0,<2.0a0, pandas >=0.24.0, plotly, python >=3.12,<3.13.0a0, python-graphviz, scipy, six
license Apache-2.0
license_family Apache
md5 457c306a5aac68d885e490c5f3d3fc65
name catboost
platform linux
sha1 37f61faf3bb4e9233bb7a3773fc290b7200dce35
sha256 fe6780c9a60bfb50fb0a4aa325b02996bb5af8d780bd4fa9a21ad7c9b6f0cf32
size 54199164
subdir linux-64
timestamp 1711453815873
version 1.2.3