- Use the `linalg::Matrix` for storing gradients.
- New API for the custom objective.
- Custom objective for multi-class/multi-target is now required to return the correct shape.
- Custom objective for Python can accept arrays with any strides. (row-major, column-major)
Added some more tests for the learner and fit_stump, for both column-wise distributed learning and vertical federated learning.
Also moved the `IsRowSplit` and `IsColumnSplit` methods from the `DMatrix` to the `MetaInfo` since in some places we only have access to the `MetaInfo`. Added a new convenience method `IsVerticalFederatedLearning`.
Some refactoring of the testing fixtures.
- Define a new tree struct embedded in the `RegTree`.
- Provide dispatching functions in `RegTree`.
- Fix some c++-17 warnings about the use of nodiscard (currently we disable the warning on
the CI).
- Use uint32_t instead of size_t for `bst_target_t` as it has a defined size and can be used
as part of dmlc parameter.
- Hide the `Segment` struct inside the categorical split matrix.
