dmlc/xgboost v1.6.1

1.6.1 Patch Release

on GitHub

v1.6.1 (2022 May 9)

This is a patch release for bug fixes and Spark barrier mode support. The R package is unchanged.

Experimental support for categorical data

• Fix segfault when the number of samples is smaller than the number of categories. (#7853)
• Enable partition-based split for all model types. (#7857)

JVM packages

We replaced the old parallelism tracker with spark barrier mode to improve the robustness of the JVM package and fix the GPU training pipeline.

• Fix GPU training pipeline quantile synchronization. (#7823, #7834)
• Use barrier model in spark package. (#7836, #7840, #7845, #7846)
• Fix shared object loading on some platforms. (#7844)

Artifacts

You can verify the downloaded packages by running this on your Unix shell:

echo "<hash> <artifact>" | shasum -a 256 --check

2633f15e7be402bad0660d270e0b9a84ad6fcfd1c690a5d454efd6d55b4e395b  ./xgboost.tar.gz