Jiaming Yuan bcc0277338
Re-implement ROC-AUC. (#6747)
* Re-implement ROC-AUC.

* Binary
* MultiClass
* LTR
* Add documents.

This PR resolves a few issues:
  - Define a value when the dataset is invalid, which can happen if there's an
  empty dataset, or when the dataset contains only positive or negative values.
  - Define ROC-AUC for multi-class classification.
  - Define weighted average value for distributed setting.
  - A correct implementation for learning to rank task.  Previous
  implementation is just binary classification with averaging across groups,
  which doesn't measure ordered learning to rank.
2021-03-20 16:52:40 +08:00
..
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This folder contains testcases for XGBoost c++ core, Python package and some other CI facilities.

Directories

  • ci_build: Test facilities for Jenkins CI and GitHub action.
  • cli: Basic test for command line executable xgboost. Most of the other command line specific tests are in Python test test_cli.py
  • cpp: Tests for C++ core, using Google test framework.
  • python: Tests for Python package, demonstrations and CLI. For how to setup the dependencies for tests, see conda files in ci_build.
  • python-gpu: Similar to python tests, but for GPU.
  • travis: CI facilities for travis.
  • distributed: Legacy tests for distributed system. Most of the distributed tests are in Python tests using dask and jvm package using spark.
  • benchmark: Legacy benchmark code. There are a number of benchmark projects for XGBoost with much better configurations.

Others

  • pytest.ini: Describes the pytest marker for python tests, some markers are generated by conftest.py file.