GitLab

* Add warning for many core systems in Windows

* Add warning for not busy cores in Windows

* Change VS -> MinGW for CRAN

* Documentation to switch to MinGW by default

* Force cmake to run twice

* Try again dual build for Rtools

* Switch to cmake for building twice

* Try with Visual Studio as default, MinGW as fallback

* Try to remove VS appropriately when failing

* Attempt to get rid of build folder first

* Switch to unlink from rm rf

* Change lib_folder correctly when VS fails

* Add README updates from Microsoft/LightGBM@1c8355c

* Update default compiler doc and add GPU online install doc

* Better GPU doc

* Fixes #610

* Not force user to install VS Runtime if VS installed

* Fix Visual Studio version solutions

* readme Helper package for R-package installation

* Fix code indentation bug

* Add warning about default compiler in Windows

* Avoid repeat

* Add Rtools requirement

* Wording to promote VS as default choice for user

* Add some stuff for README

* Bump R package version and fix license

* Attempt to add one additional option and refactor

* Add more review fixes for install.libs.R

* Undo ./../../ removal (path breaking)

* Retry again simple /../

* No print, use cat.

* add R's library file to vs project and cmake.

* support using dll built by vs.

* better search for the library file.

* remove mingw related doc .

* update document.

* Let R handle the library compile.

* try fix build from github.

* Update README.md

* cleaner build.

* fix the install problem in linux.

* Update README.md

* Update to R 3.4 and Performance Note

* Add benchmark docs

* Readme.md does not exist fix

* User can safely ignore warning message

* Fix some English stuff

* More information for installation on Linux for beginners.

* add scripts for build self-contain R-package in windows.

* add unix build.

* Update README.md

* Fix to avoid issue #176 for R package installation

* Provide installation step using devtools

* finish R's c_api

* clean code

* fix sizeof pointer in 32bit system.

* add predictor class

* add Dataset class

* format code

* add booster

* add type check for expose function

* add a simple callback

* add all callbacks

* finish the basic training logic

* update docs

* add an simple training interface

* add basic test

* adapt the changes in c_api

* add test for Dataset

* add test for custom obj/eval functions

* fix python test

* fix bug in metadata init

* fix R CMD check