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[R-package] fixed sorting issues in lgb.cv() when using a model with observation weights (fixes #2572) (#2573)

* indicate support only for the last 3 macOS versions in wheel name

* document support only for 3 newest macOS versions

* try to use _mm_prefetch anywhere

* refine

* fix bug

* remove the unneeded prefetch

* transfer and enhance test for trees_to_dataframe

* fixed bug in Python 2

* implement

* fix warning

* fix bug

* fix a bug

* remove unneed function

* fix data push bug

* fix valid data push

* fix bug for missing_type=zero

* refine split

* renames

* typo

* Update metadata.cpp

* add version for training set, for efficiently update label/weight/... during training.

* Update lgb.Booster.R

* add prefetch for dense bin

* prefetch for ordered bin

* Update meta.h

* Update meta.h

* Update dense_bin.hpp

* removed OpenMP ugly fix for Mojave as it's fixed in latest CMake

* test: switch compilers

* switch compilers back

* trees_to_df method and unit test added. PEP 8 fixes for integration.

* Co-Authored-By: Nikita Titov <nekit94-08@mail.ru>

Post-review changes

* changes from second round of reviews from striker

* third round of review. formatting and added 2 more tests

* replaced pandas dot attribute accessor with string attribute accessor

* dealt with single tree edge case and minor refactor of tests

* slight refactor for checking if tree is a single node

* implement

* better documentation

* Update include/LightGBM/config.h
Co-Authored-By: Nikita Titov <nekit94-08@mail.ru>

* Apply suggestions from code review
Co-Authored-By: Nikita Titov <nekit94-08@mail.ru>

* fix document

* regenerate docs
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* [R-package] removed TODOs in code

* [ci] added to-do to TODO comment linter

* added feature importance to JSON dump

* hotfix

* Update gbdt_model_text.cpp

* warning for init_score in save_binary

fix #2639

* Update metadata.cpp

* added info into docs
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* bump XCode version for Travis

* test: swap compilers

* Update .travis.yml

* fix predict with header

* avoid duplicated feature names

* Fix bug where small values of max_bin cause crash.

* Revert "Fix bug where small values of max_bin cause crash."

This reverts commit fe5c8e2547057c1fa5750bcddd359dd7708fab4b.

* Add auc-mu multiclass metric.

* Fix bug where scores are equal.

* Merge.

* Change name to auc_mu everywhere (instead of auc-mu).

* Fix comparison between signed and unsigned int.

* Change name to AUC-mu in docs and output messages.

* Improve test.

* Use prefix increment.

* Update R package.

* Fix style issues.

* Tidy up test code.

* Read all lines first then process.

* Allow passing AUC-mu weights directly as a list in parameters.

* Remove unused code, improve example and docs.

* clean code

* clean code

* do not modify args in fit function

* added test

I believe that this should be a typo, right?

* allow python sklearn interface's fit() to pass init_model to train()

* Fix whitespace issues, and change ordering of parameters to be backward
compatible

* Formatting fixes

* allow python sklearn interface's fit() to pass init_model to train()

* Fix whitespace issues, and change ordering of parameters to be backward
compatible

* Formatting fixes

* Recognize LGBModel objects for init_model

* simplified condition

* updated docstring

* added test

* LightGBM would hang on MPI run if only some nodes have a fatal error. The issue is that the destructor of Application calls MPI_Finalize(), which will cause the program to hand and prevent from exiting. So we move the network finalization out of the destructor and call MPI_Finalize() or MPI_Abort() based on whether there was an unhandled exception.

* Minor updates: Remove excess debug logging, whitespaces.

* Add comments for new functions.