* [jvm-packages] add hostIp and python exec for rabit tracker (#7808)
* Fix training continuation with categorical model. (#7810)
* Make sure the task is initialized before construction of tree updater.
This is a quick fix meant to be backported to 1.6, for a full fix we should pass the model
param into tree updater by reference instead.
Co-authored-by: Bobby Wang <wbo4958@gmail.com>
* [jvm-packages] unify setFeaturesCol API for XGBoostRegressor (#7784)
* [jvm-packages] add doc for xgboost4j-spark-gpu (#7779)
Co-authored-by: Jiaming Yuan <jm.yuan@outlook.com>
* [jvm-packages] remove the dep of com.fasterxml.jackson (#7791)
* [jvm-packages] xgboost4j-spark should work when featuresCols is specified (#7789)
Co-authored-by: Bobby Wang <wbo4958@gmail.com>
* Drop support for deprecated CUDA architecture.
* Check file size at release branch.
* Use 200 MB limit
Co-authored-by: Philip Hyunsu Cho <chohyu01@cs.washington.edu>
* Skip non-increasing test with external memory when subsample is used.
* Increase bin numbers for boost from prediction test. This mitigates the effect of
non-deterministic partitioning.
* Use the name `Context`.
* Pass a context object into `SetInfo`.
* Add context to proxy matrix.
* Add context to iterative DMatrix.
This is to remove the use of the default number of threads during `SetInfo` as a follow-up on
removing the global omp variable while preparing for CUDA stream semantic. Currently, XGBoost
uses the legacy CUDA stream, we will gradually remove them in the future in favor of non-blocking streams.
* Generate column matrix from gHistIndex.
* Avoid synchronization with the sparse page once the cache is written.
* Cleanups: Remove member variables/functions, change the update routine to look like approx and gpu_hist.
* Remove pruner.
Fix some tests to run in a temporary directory in case the root
directory is not writable. Note that most of tests are already
running in the temporary directory, so this PR just make them
consistent.
* Extract partitioner from hist.
* Implement categorical data support by passing the gradient index directly into the partitioner.
* Organize/update document.
* Remove code for negative hessian.
xgboost4j-spark provides 2 sets of API for setting features, one for CPU, another for GPU, which may cause confusion.
This PR removes the GPU API and adds an override CPU function setFeaturesCol to accept Array[String] parameters.
* Fix copy for cv. This prevents inserting default callbacks into the input list.
* Clarify the behavior of callbacks in training/cv.
* Fix typos in doc.
