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* fix deterministic, part2

* Apply suggestions from code review

* Add support to optimize for NDCG at a given truncation level

In order to correctly optimize for NDCG@_k_, one should exclude pairs containing both documents beyond the top-_k_ (as they don't affect NDCG@_k_ when swapped).

* Update rank_objective.hpp

* Apply suggestions from code review
Co-authored-by: Guolin Ke <guolin.ke@outlook.com>

* Update rank_objective.hpp

remove the additional branching: get high_rank and low_rank by one "if".

* Update config.h

add description to lambdarank_truncation_level parameter

* Update Parameters.rst

* Update test_sklearn.py

update expected NDCG value for a test, as it was affected by the underlying change in the algorithm

* Update test_sklearn.py

update NDCG@3 reference value

* fix R learning-to-rank tests

* Update rank_objective.hpp

* Update include/LightGBM/config.h
Co-authored-by: Guolin Ke <guolin.ke@outlook.com>

* Update Parameters.rst
Co-authored-by: Guolin Ke <guolin.ke@outlook.com>
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* Update multiclass_objective.hpp

* Apply suggestions from code review

* Update src/objective/multiclass_objective.hpp

* Apply suggestions from code review

* Update test_basic.R

* Update test_basic.R

* Update src/objective/multiclass_objective.hpp
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* Apply suggestions from code review
Co-authored-by: James Lamb <jaylamb20@gmail.com>

This reverts commit 656d2676.

* Fix loss computation

* fix test

* Optimize ranking loss computation.

* Fix loss computation

* fix test

* fixed cpplint errors

* fixed more cpplint errors

* code refactoring

* update vcproject

* refine

* fix test

* Update tests/python_package_test/test_sklearn.py

* fix test

* some refines

* more omp refactoring

* format define

* fix merge bug

* some fixes

* fix some warnings

* Apply suggestions from code review

* Apply suggestions from code review

* remove dup codes

* commit

* fix a bug

* fix bug

* reset to track changes

* refine the auto choose logic

* sort the time stats output

* fix include

* change  multi_val_bin_sparse_threshold

* add cmake

* add _mm_malloc and _mm_free for cross platform

* fix cmake bug

* timer for split

* try to fix cmake

* fix tests

* refactor DataPartition::Split

* fix test

* typo

* formating

* Revert "formating"

This reverts commit 5b8de4f7fb9d975ee23701d276a66d40ee6d4222.

* add document

* [R-package] Added tests on use of force_col_wise and force_row_wise in training (#2719)

* naming

* fix gpu code

* Update include/LightGBM/bin.h
Co-Authored-By: James Lamb <jaylamb20@gmail.com>

* Update src/treelearner/ocl/histogram16.cl

* test: swap compilers for CI

* fix omp

* not avx2

* no aligned for feature histogram

* Revert "refactor DataPartition::Split"

This reverts commit 256e6d9641ade966a1f54da1752e998a1149b6f8.

* slightly refactor data partition

* reduce the memory cost
Co-authored-by: James Lamb <jaylamb20@gmail.com>
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* Implementation of XE_NDCG loss function for ranking.

* Add citation

* Check in example usage for xe_ndcg loss.

* Seed the generator when a seed is provided in the config. Add unit-tests for xe_ndcg

* Update documentation

* Fix indentation

* Address issues raised by reviewers.

* Clean up include statements.

* Fix issues raised by reviewers.

* Regenerate parameters.rst

* Add a note to explain that reproducing xe_ndcg results requires num_threads to be one.

* Introduce objective_seed and use that in rank_xendcg instead of directly using seed

* Change default value of objective_seed

* fix many cpp lint errors

* indent

* fix bug

* fix more

* fix gpu

* more fixes

* fix bug

* fix include

* norm the lambda scores

* change default to false

* update doc

* typo

* Update Parameters.rst

* Update config.h

* Update test_sklearn.py

* Update test_sklearn.py

* Update test_sklearn.py

* Update test_sklearn.py

* Update test_sklearn.py

* Update rank_objective.hpp

* Update Parameters.rst

* Update config.h

* Update test_sklearn.py

* Update test_sklearn.py

* Update test_sklearn.py

* Lambdas and hessians need to factor sigmoid_ into the computation. Additionally, the sigmoid function has an arbitrary factor of 2 in the exponent; it is not just non-standard but the gradients are not computed correctly anyway.

* Update unit test

* Also remove a heuristic that normalizes the gradient by the difference in scores.

* Also fix unit test after removing the heuristic

* fix metric alias

* fix format

* updated docs

* simplify alias in objective function

* move the alias parsing to config.cpp

* updated docs

* fix multi-class aliases

* updated regression aliases in docs

* fixed trailing space

* add balanced bagging

* refine code

* fix format

* clarify usage only for binary application

* fix a bug when bagging with reset_config

* clean code

* added all necessary includes - fixed build/include_what_you_use error

* fixed the order of includes (build/include_order)

* always save the score of the first round in early stopping

fix #1971

* avoid using std::log on non-positive numbers

* remove unnecessary changes

* add tests

* Update test_sklearn.py

* enhanced tests

* fix RF's bugs

* fix tests

* rollback num_iterations

* fix a bug and reduce memory costs

* reduce memory cost

* fix ndcg consistency.

* more stable sorts

* Update gbdt_model_text.cpp

* Update dataset.cpp

* Update gbdt_model_text.cpp

* average predictions for constant features

* fix possible numerical issues in std::log.

* fix pylint

* fix bugs in c_api

* fix styles

* clean code for multi class

* rewrite test

* fix pylint

* skip test_constant_features

* refine test

* fix tests

* fix tests

* update FAQ

* fix test

* Update FAQ.rst