* Remove R check from Jenkins
* Print stacktrace when CRAN test fail in GitHub Actions
* Add verbose flag in tests/ci_build/print_r_stacktrace.sh
* Fix path in tests/ci_build/print_r_stacktrace.sh
* Make external memory data partitioning deterministic.
* Change the meaning of `page_size` from bytes to number of rows.
* Design a data pool.
* Note for external memory.
* Enable unity build on Windows CI.
* Force garbage collect on test.
This PR is meant the end the confusion around best_ntree_limit and unify model slicing. We have multi-class and random forests, asking users to understand how to set ntree_limit is difficult and error prone.
* Implement the save_best option in early stopping.
Co-authored-by: Philip Hyunsu Cho <chohyu01@cs.washington.edu>
* Removed some warnings
* Rebase with master
* Solved C++ Google Tests errors made by refactoring in order to remove warnings
* Undo renaming path -> path_
* Fix style check
Co-authored-by: Hyunsu Cho <chohyu01@cs.washington.edu>
CLI is not most developed interface. Putting them into correct directory can help new users to avoid it as most of the use cases are from a language binding.
* Deprecate LabelEncoder in XGBClassifier; skip LabelEncoder for cuDF/cuPy inputs
* Add unit tests for cuDF and cuPy inputs with XGBClassifier
* Fix lint
* Clarify warning
* Move use_label_encoder option to XGBClassifier constructor
* Add a test for cudf.Series
* Add use_label_encoder to XGBRFClassifier doc
* Address reviewer feedback
* Disable JSON serialization for now.
* Multi-class classification is checkpointing for each iteration.
This brings significant overhead.
Revert: 90355b4f007ae
* Set R tests to use binary.
* [CI] Clean up build for JVM packages
* Use correct path for saving native lib
* Fix groupId of maven-surefire-plugin
* Fix stashing of xgboost4j_jar_gpu
* [CI] Don't run xgboost4j-tester with GPU, since it doesn't use gpu_hist
* Change DefaultEvalMetric of classification from error to logloss
* Change default binary metric in plugin/example/custom_obj.cc
* Set old error metric in python tests
* Set old error metric in R tests
* Fix missed eval metrics and typos in R tests
* Fix setting eval_metric twice in R tests
* Add warning for empty eval_metric for classification
* Fix Dask tests
Co-authored-by: Hyunsu Cho <chohyu01@cs.washington.edu>
