GitLab

* added cpplint heck

* removed TODO from code

* change order of checks

* added fix for OpenMP on macOS into test script

* test: AppleClang on Travis

* use Mojave on Travis

* bash hotfix

* get back to gcc compiler on Travis macOS

* removed brew hotfix and deprecated sudo option on Travis

* removed brew hotfix on Azure

* fixed xcode version

* fixed brew on Travis

* fixed brew on Azure Pipelines

* using different version for master branch with release

* Update .travis.yml

* Update .travis.yml

* reorganized CI files

* merged scripts into one

* refined Travis tests

* refined VSTS Linux part

* cleanup

* added possibility to test Clang at VSTS

* simplified cp command

* Fix CI (#1652)

* Update .travis.yml

* Update .appveyor.yml

* only tags for build

* Update .vsts-ci.yml

* Update .vsts-ci.yml

* added python 3.7 to the list of supporting versions

* reorganized python versions at Travis

* addressed review comments

* added clang test

* hotfix

* downgrade required AppleCLang version

* fixed CMakeLists

* prevent case when CMake is downgraded by libomp

* fixed Clang test

* moved MSVC version check to the better place

* compile with Clang at Travis on Linux

* clear .travis.yml

* fixed indents

* added support of MPI test at Travis with macOS

* added FAQ entry about OpenMP library error

* updated installation guide

* moved APPLE_OUTPUT_DYLIB to other options

* fix check-docs test: ignore old url from error message

* added example of symlink command in FAQ

* fixed markdown

* capitalized heading

* updated Python installation guide

* changed mode in message command

* added notes about MinGW efficiency problems

* updated R-package installation guide

* use quotes for gcc version

* removed excess 'Note' phrase

* bring gpu tests back

* corrected docs according to the news that AMD drops the support of AMD APP SDK

* replaced link to AMD APP SDK

* fixed downloading AMD APP SDK from GitHub without auth

* fixed path tp AMD APP SDK in docs

* removed exports

* clarify AMD APP SDK package installation condition

* remove protobuf

* add version number

* remove pmml script

* use float for split gain

* fix warnings

* refine the read model logic of gbdt

* fix compile error

* improve decode speed

* fix some bugs

* fix double accuracy problem

* fix bug

* multi-thread save model

* speed up save model to string

* parallel save/load model

* fix some warnings.

* fix warnings.

* fix a bug

* remove debug output

* fix doc

* fix max_bin warning in tests.

* fix max_bin warning

* fix pylint

* clean code for stringToArray

* clean code for TToString

* remove max_bin

* replace "class" with typename

* [optional] support protobuf

* fix windows/LightGBM.vcxproj

* add doc

* fix doc

* fix vs support (#2)

* fix vs support

* fix cmake

This reverts commit 53b99854.

* added doc test

* fixed 404

* prevented maito: ref creation

* added rst structure test

* fixed unknown directives

* added code for the future check for html syntax

* replaced problem link

* add python examples to test [test should fail]

* fix example && move some to advanced_example

* fix last line

* refine test python version

* travis cleanup

* removed precompiled files in windows folder from sdist command

* removed rubbish from install folder

* added compute folder

* disabled logs from compilers; fixed #874

* fixed safe clear_fplder

* added windows folder to manifest.in

* added windows folder to build

* added library path

* added compilation with MSBuild from .sln-file

* fixed unknown PlatformToolset returns exitcode 0

* hotfix

* updated Readme

* removed return

* added installation with mingw test to appveyor

* let's test appveyor with both VS 2015 and VS 2017; but MinGW isn't installed on VS 2017 image

* fixed built-in name 'file'

* simplified appveyor

* removed excess data_files

* fixed unreadable paths

* separated exceptions for cmake and mingw

* refactored silent_call

* don't create artifacts with VS 2015 and mingw

* be more precise with python versioning in Travis

* removed unnecessary if statement

* added classifiers for PyPI and python versions badge

* changed python version in travis

* added support of scikit-learn 0.18.x

* added more python versions to Travis

* added more python versions to Appveyor

* reduced number of tests in Travis

* Travis trick is not needed anymore

* attempt to fix according to https://github.com/Microsoft/LightGBM/pull/880#discussion_r137438856

* setup.py custom install & sdist

* global data_files

* fix install rule

* fix pylint

* clean codes

* use distutils.command

* overwrite install_lib

* add copy_files; fix pylint

* install openmpi only TASK=mpi

* add TASK=sdist & bdist

* setuptools.command instead of distutils

* add METHOD=pip for gpu test

* use openmpi to install gcc

* set OpenCL_INCLUDE_DIR & BOOST_ROOT

* update doc

* export BOOST_ROOT

* update doc

* update doc

* update doc

* support travis osx

* add task=pip

* add osx task=pip

* fix gpu build

* add if-else task

* fix if-else task

* add make command to the python package.

* Update README.rst

* Update README.rst

* Update README.rst

* fix tests.

* fix unix build

* update readme

* fix setup.py

* update travis

* Update .travis.yml

* Update test.py

* some fixes.

* check the 64-bit python

* fix build.

* refine MANIFEST.in

* update Manifest.in

* add more build options.

* Add fatal in cmake

* fix a endif.

* fix bugs.

* fix pep8

* add test for the pip package build

* add test pip install in travis.

* fix version with pre-compile dll

* fix readme.rst

* update readme

https://docs.pytest.org/

* docs: move files into general

* docs: initial commit for Read the Docs

http://docs.readthedocs.io/en/latest/getting_started.html

just running `sphinx-quickstart`

* docs: update conf.py

* docs: add requirements.txt

* docs: add README.md

* fix tests

* docs: put original docs back

* auto replace gbdt::prediction

* add test if_else_prediction

* not override gbdt_prediction.cpp

* close ifstream

* re-order .travis.yml

* Revert "python-package: support valid_names in scikit-learn API (#420)"

This reverts commit de39dbcf.

* Revert "faster histogram sum up (#418)"

This reverts commit 98c7c2a3.

* some refactor.

* two stage sum up to reduce sum up error.

* add more two-stage sumup.

* some refactor.

* add alignment.

* change name to aligned_allocator.

* remove some useless sumup.

* fix a warning.

* add -march=native .

* remove the padding of gradients.

* no alignment.

* fix test.

* change KNumSumupGroup to 32768.

* change gcc flags.

* add dummy gpu solver code

* initial GPU code

* fix crash bug

* first working version

* use asynchronous copy

* use a better kernel for root

* parallel read histogram

* sparse features now works, but no acceleration, compute on CPU

* compute sparse feature on CPU simultaneously

* fix big bug; add gpu selection; add kernel selection

* better debugging

* clean up

* add feature scatter

* Add sparse_threshold control

* fix a bug in feature scatter

* clean up debug

* temporarily add OpenCL kernels for k=64,256

* fix up CMakeList and definition USE_GPU

* add OpenCL kernels as string literals

* Add boost.compute as a submodule

* add boost dependency into CMakeList

* fix opencl pragma

* use pinned memory for histogram

* use pinned buffer for gradients and hessians

* better debugging message

* add double precision support on GPU

* fix boost version in CMakeList

* Add a README

* reconstruct GPU initialization code for ResetTrainingData

* move data to GPU in parallel

* fix a bug during feature copy

* update gpu kernels

* update gpu code

* initial port to LightGBM v2

* speedup GPU data loading process

* Add 4-bit bin support to GPU

* re-add sparse_threshold parameter

* remove kMaxNumWorkgroups and allows an unlimited number of features

* add feature mask support for skipping unused features

* enable kernel cache

* use GPU kernels withoug feature masks when all features are used

* REAdme.

* REAdme.

* update README

* fix typos (#349)

* change compile to gcc on Apple as default

* clean vscode related file

* refine api of constructing from sampling data.

* fix bug in the last commit.

* more efficient algorithm to sample k from n.

* fix bug in filter bin

* change to boost from average output.

* fix tests.

* only stop training when all classes are finshed in multi-class.

* limit the max tree output. change hessian in multi-class objective.

* robust tree model loading.

* fix test.

* convert the probabilities to raw score in boost_from_average of classification.

* fix the average label for binary classification.

* Add boost_from_average to docs (#354)

* don't use "ConvertToRawScore" for self-defined objective function.

* boost_from_average seems doesn't work well in binary classification. remove it.

* For a better jump link (#355)

* Update Python-API.md

* for a better jump in page

A space is needed between `#` and the headers content according to Github's markdown format [guideline](https://guides.github.com/features/mastering-markdown/)

After adding the spaces, we can jump to the exact position in page by click the link.

* fixed something mentioned by @wxchan

* Update Python-API.md

* add FitByExistingTree.

* adapt GPU tree learner for FitByExistingTree

* avoid NaN output.

* update boost.compute

* fix typos (#361)

* fix broken links (#359)

* update README

* disable GPU acceleration by default

* fix image url

* cleanup debug macro

* remove old README

* do not save sparse_threshold_ in FeatureGroup

* add details for new GPU settings

* ignore submodule when doing pep8 check

* allocate workspace for at least one thread during builing Feature4

* move sparse_threshold to class Dataset

* remove duplicated code in GPUTreeLearner::Split

* Remove duplicated code in FindBestThresholds and BeforeFindBestSplit

* do not rebuild ordered gradients and hessians for sparse features

* support feature groups in GPUTreeLearner

* Initial parallel learners with GPU support

* add option device, cleanup code

* clean up FindBestThresholds; add some omp parallel

* constant hessian optimization for GPU

* Fix GPUTreeLearner crash when there is zero feature

* use np.testing.assert_almost_equal() to compare lists of floats in tests

* travis for GPU