* Implement multi-target for hist.
- Add new hist tree builder.
- Move data fetchers for tests.
- Dispatch function calls in gbm base on the tree type.
* Extract most of the functionality into `DMatrixCache`.
* Move API entry to independent file to reduce dependency on `predictor.h` file.
* Add test.
---------
Co-authored-by: Philip Hyunsu Cho <chohyu01@cs.washington.edu>
* Use array interface for CSC matrix.
Use array interface for CSC matrix and align the interface with CSR and dense.
- Fix nthread issue in the R package DMatrix.
- Unify the behavior of handling `missing` with other inputs.
- Unify the behavior of handling `missing` around R, Python, Java, and Scala DMatrix.
- Expose `num_non_missing` to the JVM interface.
- Deprecate old CSR and CSC constructors.
* [R] Use new interface for creating DMatrix from CSR.
- CSC is still using the old API.
The old API is not aware of `nthread` parameter, which makes DMatrix to use all available
thread during construction and during transformation lie `SparsePage` -> `CSCPage`.
- Group C API.
- Add C API sphinx doc.
- Consistent use of `OptionalArg` and the parameter name `config`.
- Remove call to deprecated functions in demo.
- Fix some formatting errors.
- Add links to c examples in the document (only visible with doxygen pages)
- Fix arrow.
Federated learning plugin for xgboost:
* A gRPC server to aggregate MPI-style requests (allgather, allreduce, broadcast) from federated workers.
* A Rabit engine for the federated environment.
* Integration test to simulate federated learning.
Additional followups are needed to address GPU support, better security, and privacy, etc.
* 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.
* [R] Fix global feature importance.
* Add implementation for tree index. The parameter is not documented in C API since we
should work on porting the model slicing to R instead of supporting more use of tree
index.
* Fix the difference between "gain" and "total_gain".
* debug.
* Fix prediction.
- Reduce dependency on dmlc parsers and provide an interface for users to load data by themselves.
- Remove use of threaded iterator and IO queue.
- Remove `page_size`.
- Make sure the number of pages in memory is bounded.
- Make sure the cache can not be violated.
- Provide an interface for internal algorithms to process data asynchronously.
The role of ProxyDMatrix is going beyond what it was designed. Now it's used by both
QuantileDeviceDMatrix and inplace prediction. After the refactoring of sparse DMatrix it
will also be used for external memory. Renaming the C API to extract it from
QuantileDeviceDMatrix.
* Add feature score support for linear model.
* Port R interface to the new implementation.
* Add linear model support in Python.
Co-authored-by: Philip Hyunsu Cho <chohyu01@cs.washington.edu>
