From 94fbe5bb9fbb5f6067821f0be9cd145f0b7d7d94 Mon Sep 17 00:00:00 2001 From: Guolin Ke Date: Wed, 8 May 2019 13:51:28 +0800 Subject: [PATCH] [docs] updated Microsoft GitHub URL (#2152) * fix travis badge * updated GitHub Microsoft URL --- .appveyor.yml | 4 +- .ci/setup.sh | 2 +- .nuget/create_nuget.py | 4 +- R-package/README.md | 14 +- R-package/demo/efficient_many_training.R | 2 +- R-package/demo/multiclass_custom_objective.R | 2 +- README.md | 46 ++-- docker/gpu/dockerfile.gpu | 2 +- docs/Development-Guide.rst | 6 +- docs/FAQ.rst | 26 +-- docs/GPU-Performance.rst | 2 +- docs/GPU-Targets.rst | 2 +- docs/GPU-Tutorial.rst | 4 +- docs/GPU-Windows.rst | 4 +- docs/Installation-Guide.rst | 54 ++--- docs/Key-Events.md | 224 +++++++++---------- docs/Parallel-Learning-Guide.rst | 2 +- docs/Parameters.rst | 2 +- docs/Python-Intro.rst | 4 +- docs/Quick-Start.rst | 8 +- docs/README.rst | 4 +- examples/README.md | 2 +- examples/parallel_learning/README.md | 2 +- examples/python-guide/README.md | 12 +- include/LightGBM/config.h | 2 +- python-package/README.rst | 22 +- python-package/lightgbm/__init__.py | 2 +- python-package/setup.py | 2 +- tests/python_package_test/test_sklearn.py | 2 +- windows/LightGBM.sln | 2 +- windows/LightGBM.vcxproj | 4 +- windows/LightGBM.vcxproj.filters | 4 +- 32 files changed, 237 insertions(+), 237 deletions(-) diff --git a/.appveyor.yml b/.appveyor.yml index cba4f1c247e..dac39ec2556 100644 --- a/.appveyor.yml +++ b/.appveyor.yml @@ -1,4 +1,4 @@ -version: 2.2.4.{build} +version: 2.2.4.{build} image: Visual Studio 2015 platform: x64 @@ -44,7 +44,7 @@ test_script: - pytest %APPVEYOR_BUILD_FOLDER%\tests\python_package_test - cd %APPVEYOR_BUILD_FOLDER%\examples\python-guide - ps: >- - @("import matplotlib", "matplotlib.use('Agg')") + (Get-Content "plot_example.py") | Set-Content "plot_example.py" # prevent interactive window mode + @("import matplotlib", "matplotlib.use('Agg')") + (Get-Content "plot_example.py") | Set-Content "plot_example.py" # prevent interactive window mode (Get-Content "plot_example.py").replace('graph.render(view=True)', 'graph.render(view=False)') | Set-Content "plot_example.py" - ps: >- foreach ($file in @(Get-ChildItem *.py)) { diff --git a/.ci/setup.sh b/.ci/setup.sh index 4ac70b35e7e..1c2ba423939 100755 --- a/.ci/setup.sh +++ b/.ci/setup.sh @@ -34,7 +34,7 @@ else # Linux sudo apt-get update sudo apt-get install --no-install-recommends -y libboost1.68-dev ocl-icd-opencl-dev cd $BUILD_DIRECTORY # to avoid permission errors - wget -q https://github.com/Microsoft/LightGBM/releases/download/v2.0.12/AMD-APP-SDKInstaller-v3.0.130.136-GA-linux64.tar.bz2 + wget -q https://github.com/microsoft/LightGBM/releases/download/v2.0.12/AMD-APP-SDKInstaller-v3.0.130.136-GA-linux64.tar.bz2 tar -xjf AMD-APP-SDK*.tar.bz2 mkdir -p $OPENCL_VENDOR_PATH mkdir -p $AMDAPPSDK_PATH diff --git a/.nuget/create_nuget.py b/.nuget/create_nuget.py index bc9cb371be1..666e4708ce8 100644 --- a/.nuget/create_nuget.py +++ b/.nuget/create_nuget.py @@ -34,8 +34,8 @@ %s Guolin Ke Guolin Ke - https://github.com/Microsoft/LightGBM/blob/master/LICENSE - https://github.com/Microsoft/LightGBM + https://github.com/microsoft/LightGBM/blob/master/LICENSE + https://github.com/microsoft/LightGBM false A fast, distributed, high performance gradient boosting framework Copyright %d @ Microsoft diff --git a/R-package/README.md b/R-package/README.md index 5fe42ac6a49..1b9531d1533 100644 --- a/R-package/README.md +++ b/R-package/README.md @@ -24,7 +24,7 @@ For users who wants to install online with GPU or want to choose a specific comp #### Mac OS Preparation -You can perform installation either with **Apple Clang** or **gcc**. In case you prefer **Apple Clang**, you should install **OpenMP** (details for installation can be found in [Installation Guide](https://github.com/Microsoft/LightGBM/blob/master/docs/Installation-Guide.rst#apple-clang)) first and **CMake** version 3.12 or higher is required. In case you prefer **gcc**, you need to install it (details for installation can be found in [Installation Guide](https://github.com/Microsoft/LightGBM/blob/master/docs/Installation-Guide.rst#gcc)) and set some environment variables to tell R to use `gcc` and `g++`. If you install these from Homebrew, your versions of `g++` and `gcc` are most likely in `/usr/local/bin`, as shown below. +You can perform installation either with **Apple Clang** or **gcc**. In case you prefer **Apple Clang**, you should install **OpenMP** (details for installation can be found in [Installation Guide](https://github.com/microsoft/LightGBM/blob/master/docs/Installation-Guide.rst#apple-clang)) first and **CMake** version 3.12 or higher is required. In case you prefer **gcc**, you need to install it (details for installation can be found in [Installation Guide](https://github.com/microsoft/LightGBM/blob/master/docs/Installation-Guide.rst#gcc)) and set some environment variables to tell R to use `gcc` and `g++`. If you install these from Homebrew, your versions of `g++` and `gcc` are most likely in `/usr/local/bin`, as shown below. ``` # replace 8 with version of gcc installed on your machine @@ -36,7 +36,7 @@ export CXX=/usr/local/bin/g++-8 CC=/usr/local/bin/gcc-8 Build and install R-package with the following commands: ```sh -git clone --recursive https://github.com/Microsoft/LightGBM +git clone --recursive https://github.com/microsoft/LightGBM cd LightGBM Rscript build_r.R ``` @@ -47,7 +47,7 @@ Note: for the build with Visual Studio/VS Build Tools in Windows, you should use Windows users may need to run with administrator rights (either R or the command prompt, depending on the way you are installing this package). Linux users might require the appropriate user write permissions for packages. -Set `use_gpu` to `TRUE` in `R-package/src/install.libs.R` to enable the build with GPU support. You will need to install Boost and OpenCL first: details for installation can be found in [Installation-Guide](https://github.com/Microsoft/LightGBM/blob/master/docs/Installation-Guide.rst#build-gpu-version). +Set `use_gpu` to `TRUE` in `R-package/src/install.libs.R` to enable the build with GPU support. You will need to install Boost and OpenCL first: details for installation can be found in [Installation-Guide](https://github.com/microsoft/LightGBM/blob/master/docs/Installation-Guide.rst#build-gpu-version). If you are using a precompiled dll/lib locally, you can move the dll/lib into LightGBM root folder, modify `LightGBM/R-package/src/install.libs.R`'s 2nd line (change `use_precompile <- FALSE` to `use_precompile <- TRUE`), and install R-package as usual. **NOTE: If your R version is not smaller than 3.5.0, you should set `DUSE_R35=ON` in cmake options when build precompiled dll/lib**. @@ -89,7 +89,7 @@ For instance, you can install the R-package from LightGBM master commit of GitHu ```r lgb.dl(commit = "master", compiler = "vs", - repo = "https://github.com/Microsoft/LightGBM") + repo = "https://github.com/microsoft/LightGBM") ``` You may also install using a precompiled dll/lib using the following from R: @@ -97,7 +97,7 @@ You may also install using a precompiled dll/lib using the following from R: ```r lgb.dl(commit = "master", libdll = "C:\\LightGBM\\windows\\x64\\DLL\\lib_lightgbm.dll", # YOUR PRECOMPILED DLL - repo = "https://github.com/Microsoft/LightGBM") + repo = "https://github.com/microsoft/LightGBM") ``` You may also install online using a LightGBM with proper GPU support using Visual Studio (as an example here) using the following from R: @@ -105,13 +105,13 @@ You may also install online using a LightGBM with proper GPU support using Visua ```r lgb.dl(commit = "master", compiler = "vs", # Remove this for MinGW + GPU installation - repo = "https://github.com/Microsoft/LightGBM", + repo = "https://github.com/microsoft/LightGBM", use_gpu = TRUE) ``` For more details about options, please check [Laurae2/lgbdl](https://github.com/Laurae2/lgbdl/) R-package. -You may also read [Microsoft/LightGBM#912](https://github.com/Microsoft/LightGBM/issues/912#issuecomment-329496254) for a visual example for LightGBM installation in Windows with Visual Studio. +You may also read [Microsoft/LightGBM#912](https://github.com/microsoft/LightGBM/issues/912#issuecomment-329496254) for a visual example for LightGBM installation in Windows with Visual Studio. Examples -------- diff --git a/R-package/demo/efficient_many_training.R b/R-package/demo/efficient_many_training.R index 6a63797e4ae..0e11a13b38e 100644 --- a/R-package/demo/efficient_many_training.R +++ b/R-package/demo/efficient_many_training.R @@ -2,7 +2,7 @@ # In the case of many trainings (like 100+ models), RAM will be eaten very quickly # Therefore, it is essential to know a strategy to deal with such issue -# More results can be found here: https://github.com/Microsoft/LightGBM/issues/879#issuecomment-326656580 +# More results can be found here: https://github.com/microsoft/LightGBM/issues/879#issuecomment-326656580 # Quote: "@Laurae2 Thanks for nice easily reproducible example (unlike mine). # With reset=FALSE you get after 500 iterations (not 1000): OS reports 27GB usage, while R gc() reports 1.5GB. # Just doing reset=TRUE will already improve things: OS reports 4.6GB. diff --git a/R-package/demo/multiclass_custom_objective.R b/R-package/demo/multiclass_custom_objective.R index f7f0a5c296b..ccceca70a86 100644 --- a/R-package/demo/multiclass_custom_objective.R +++ b/R-package/demo/multiclass_custom_objective.R @@ -19,7 +19,7 @@ valids <- list(train = dtrain, test = dtest) # Method 1 of training with built-in multiclass objective # Note: need to turn off boost from average to match custom objective -# (https://github.com/Microsoft/LightGBM/issues/1846) +# (https://github.com/microsoft/LightGBM/issues/1846) model_builtin <- lgb.train(list(), dtrain, boost_from_average = FALSE, diff --git a/README.md b/README.md index e575cd9d25a..63cac8df51f 100644 --- a/README.md +++ b/README.md @@ -3,10 +3,10 @@ LightGBM, Light Gradient Boosting Machine [![Azure Pipelines Build Status](https://lightgbm-ci.visualstudio.com/lightgbm-ci/_apis/build/status/Microsoft.LightGBM?branchName=master)](https://lightgbm-ci.visualstudio.com/lightgbm-ci/_build/latest?definitionId=1) [![Appveyor Build Status](https://ci.appveyor.com/api/projects/status/1ys5ot401m0fep6l/branch/master?svg=true)](https://ci.appveyor.com/project/guolinke/lightgbm/branch/master) -[![Travis Build Status](https://travis-ci.org/Microsoft/LightGBM.svg?branch=master)](https://travis-ci.org/Microsoft/LightGBM) +[![Travis Build Status](https://travis-ci.org/microsoft/LightGBM.svg?branch=master)](https://travis-ci.org/microsoft/LightGBM) [![Documentation Status](https://readthedocs.org/projects/lightgbm/badge/?version=latest)](https://lightgbm.readthedocs.io/) -[![GitHub Issues](https://img.shields.io/github/issues/Microsoft/LightGBM.svg)](https://github.com/Microsoft/LightGBM/issues) -[![License](https://img.shields.io/badge/license-MIT-blue.svg)](https://github.com/Microsoft/LightGBM/blob/master/LICENSE) +[![GitHub Issues](https://img.shields.io/github/issues/Microsoft/LightGBM.svg)](https://github.com/microsoft/LightGBM/issues) +[![License](https://img.shields.io/badge/license-MIT-blue.svg)](https://github.com/microsoft/LightGBM/blob/master/LICENSE) [![Python Versions](https://img.shields.io/pypi/pyversions/lightgbm.svg)](https://pypi.org/project/lightgbm) [![PyPI Version](https://img.shields.io/pypi/v/lightgbm.svg)](https://pypi.org/project/lightgbm) [![Join the chat at https://gitter.im/Microsoft/LightGBM](https://badges.gitter.im/Microsoft/LightGBM.svg)](https://gitter.im/Microsoft/LightGBM?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge) @@ -20,11 +20,11 @@ LightGBM is a gradient boosting framework that uses tree based learning algorith - Support of parallel and GPU learning. - Capable of handling large-scale data. -For further details, please refer to [Features](https://github.com/Microsoft/LightGBM/blob/master/docs/Features.rst). +For further details, please refer to [Features](https://github.com/microsoft/LightGBM/blob/master/docs/Features.rst). -Benefitting from these advantages, LightGBM is being widely-used in many [winning solutions](https://github.com/Microsoft/LightGBM/blob/master/examples/README.md#machine-learning-challenge-winning-solutions) of machine learning competitions. +Benefitting from these advantages, LightGBM is being widely-used in many [winning solutions](https://github.com/microsoft/LightGBM/blob/master/examples/README.md#machine-learning-challenge-winning-solutions) of machine learning competitions. -[Comparison experiments](https://github.com/Microsoft/LightGBM/blob/master/docs/Experiments.rst#comparison-experiment) on public datasets show that LightGBM can outperform existing boosting frameworks on both efficiency and accuracy, with significantly lower memory consumption. What's more, [parallel experiments](https://github.com/Microsoft/LightGBM/blob/master/docs/Experiments.rst#parallel-experiment) show that LightGBM can achieve a linear speed-up by using multiple machines for training in specific settings. +[Comparison experiments](https://github.com/microsoft/LightGBM/blob/master/docs/Experiments.rst#comparison-experiment) on public datasets show that LightGBM can outperform existing boosting frameworks on both efficiency and accuracy, with significantly lower memory consumption. What's more, [parallel experiments](https://github.com/microsoft/LightGBM/blob/master/docs/Experiments.rst#parallel-experiment) show that LightGBM can achieve a linear speed-up by using multiple machines for training in specific settings. News ---- @@ -45,13 +45,13 @@ News 02/12/2017 : LightGBM v1 stable release. -01/08/2017 : Release [**R-package**](https://github.com/Microsoft/LightGBM/tree/master/R-package) beta version, welcome to have a try and provide feedback. +01/08/2017 : Release [**R-package**](https://github.com/microsoft/LightGBM/tree/master/R-package) beta version, welcome to have a try and provide feedback. 12/05/2016 : **Categorical Features as input directly** (without one-hot coding). -12/02/2016 : Release [**Python-package**](https://github.com/Microsoft/LightGBM/tree/master/python-package) beta version, welcome to have a try and provide feedback. +12/02/2016 : Release [**Python-package**](https://github.com/microsoft/LightGBM/tree/master/python-package) beta version, welcome to have a try and provide feedback. -More detailed update logs : [Key Events](https://github.com/Microsoft/LightGBM/blob/master/docs/Key-Events.md). +More detailed update logs : [Key Events](https://github.com/microsoft/LightGBM/blob/master/docs/Key-Events.md). External (Unofficial) Repositories ---------------------------------- @@ -77,22 +77,22 @@ Dask-LightGBM (distributed and parallel Python-package): https://github.com/dask Get Started and Documentation ----------------------------- -Install by following [guide](https://github.com/Microsoft/LightGBM/blob/master/docs/Installation-Guide.rst) for the command line program, [Python-package](https://github.com/Microsoft/LightGBM/tree/master/python-package) or [R-package](https://github.com/Microsoft/LightGBM/tree/master/R-package). Then please see the [Quick Start](https://github.com/Microsoft/LightGBM/blob/master/docs/Quick-Start.rst) guide. +Install by following [guide](https://github.com/microsoft/LightGBM/blob/master/docs/Installation-Guide.rst) for the command line program, [Python-package](https://github.com/microsoft/LightGBM/tree/master/python-package) or [R-package](https://github.com/microsoft/LightGBM/tree/master/R-package). Then please see the [Quick Start](https://github.com/microsoft/LightGBM/blob/master/docs/Quick-Start.rst) guide. Our primary documentation is at https://lightgbm.readthedocs.io/ and is generated from this repository. Next you may want to read: -* [**Examples**](https://github.com/Microsoft/LightGBM/tree/master/examples) showing command line usage of common tasks. -* [**Features**](https://github.com/Microsoft/LightGBM/blob/master/docs/Features.rst) and algorithms supported by LightGBM. -* [**Parameters**](https://github.com/Microsoft/LightGBM/blob/master/docs/Parameters.rst) is an exhaustive list of customization you can make. -* [**Parallel Learning**](https://github.com/Microsoft/LightGBM/blob/master/docs/Parallel-Learning-Guide.rst) and [**GPU Learning**](https://github.com/Microsoft/LightGBM/blob/master/docs/GPU-Tutorial.rst) can speed up computation. +* [**Examples**](https://github.com/microsoft/LightGBM/tree/master/examples) showing command line usage of common tasks. +* [**Features**](https://github.com/microsoft/LightGBM/blob/master/docs/Features.rst) and algorithms supported by LightGBM. +* [**Parameters**](https://github.com/microsoft/LightGBM/blob/master/docs/Parameters.rst) is an exhaustive list of customization you can make. +* [**Parallel Learning**](https://github.com/microsoft/LightGBM/blob/master/docs/Parallel-Learning-Guide.rst) and [**GPU Learning**](https://github.com/microsoft/LightGBM/blob/master/docs/GPU-Tutorial.rst) can speed up computation. * [**Laurae++ interactive documentation**](https://sites.google.com/view/lauraepp/parameters) is a detailed guide for hyperparameters. Documentation for contributors: -* [**How we update readthedocs.io**](https://github.com/Microsoft/LightGBM/blob/master/docs/README.rst). -* Check out the [**Development Guide**](https://github.com/Microsoft/LightGBM/blob/master/docs/Development-Guide.rst). +* [**How we update readthedocs.io**](https://github.com/microsoft/LightGBM/blob/master/docs/README.rst). +* Check out the [**Development Guide**](https://github.com/microsoft/LightGBM/blob/master/docs/Development-Guide.rst). Support ------- @@ -101,18 +101,18 @@ Support * Discuss on the [LightGBM Gitter](https://gitter.im/Microsoft/LightGBM). * Discuss on the [LightGBM Slack team](https://lightgbm.slack.com). * Use [this invite link](https://lightgbm-slack-autojoin.herokuapp.com/) to join the team. -* Open **bug reports** and **feature requests** (not questions) on [GitHub issues](https://github.com/Microsoft/LightGBM/issues). +* Open **bug reports** and **feature requests** (not questions) on [GitHub issues](https://github.com/microsoft/LightGBM/issues). How to Contribute ----------------- LightGBM has been developed and used by many active community members. Your help is very valuable to make it better for everyone. -- Check out [call for contributions](https://github.com/Microsoft/LightGBM/issues?q=is%3Aissue+is%3Aopen+label%3Acall-for-contribution) to see what can be improved, or open an issue if you want something. -- Contribute to the [tests](https://github.com/Microsoft/LightGBM/tree/master/tests) to make it more reliable. -- Contribute to the [documents](https://github.com/Microsoft/LightGBM/tree/master/docs) to make it clearer for everyone. -- Contribute to the [examples](https://github.com/Microsoft/LightGBM/tree/master/examples) to share your experience with other users. -- Add your stories and experience to [Awesome LightGBM](https://github.com/Microsoft/LightGBM/blob/master/examples/README.md). +- Check out [call for contributions](https://github.com/microsoft/LightGBM/issues?q=is%3Aissue+is%3Aopen+label%3Acall-for-contribution) to see what can be improved, or open an issue if you want something. +- Contribute to the [tests](https://github.com/microsoft/LightGBM/tree/master/tests) to make it more reliable. +- Contribute to the [documents](https://github.com/microsoft/LightGBM/tree/master/docs) to make it clearer for everyone. +- Contribute to the [examples](https://github.com/microsoft/LightGBM/tree/master/examples) to share your experience with other users. +- Add your stories and experience to [Awesome LightGBM](https://github.com/microsoft/LightGBM/blob/master/examples/README.md). - Open issue if you met problems during development. Microsoft Open Source Code of Conduct @@ -132,4 +132,4 @@ Huan Zhang, Si Si and Cho-Jui Hsieh. "[GPU Acceleration for Large-scale Tree Boo License ------- -This project is licensed under the terms of the MIT license. See [LICENSE](https://github.com/Microsoft/LightGBM/blob/master/LICENSE) for additional details. +This project is licensed under the terms of the MIT license. See [LICENSE](https://github.com/microsoft/LightGBM/blob/master/LICENSE) for additional details. diff --git a/docker/gpu/dockerfile.gpu b/docker/gpu/dockerfile.gpu index e54595e0951..84fba4b8f70 100644 --- a/docker/gpu/dockerfile.gpu +++ b/docker/gpu/dockerfile.gpu @@ -82,7 +82,7 @@ RUN conda create -q -n py3 python=3.5 mkl numpy scipy scikit-learn jupyter noteb ################################################################################################################# RUN cd /usr/local/src && mkdir lightgbm && cd lightgbm && \ - git clone --recursive https://github.com/Microsoft/LightGBM && \ + git clone --recursive https://github.com/microsoft/LightGBM && \ cd LightGBM && mkdir build && cd build && \ cmake -DUSE_GPU=1 -DOpenCL_LIBRARY=/usr/local/cuda/lib64/libOpenCL.so -DOpenCL_INCLUDE_DIR=/usr/local/cuda/include/ .. && \ make OPENCL_HEADERS=/usr/local/cuda-8.0/targets/x86_64-linux/include LIBOPENCL=/usr/local/cuda-8.0/targets/x86_64-linux/lib diff --git a/docs/Development-Guide.rst b/docs/Development-Guide.rst index bc74b8ed67f..d7446ca2e90 100644 --- a/docs/Development-Guide.rst +++ b/docs/Development-Guide.rst @@ -73,16 +73,16 @@ Refer to `docs README <./README.rst>`__. C API ----- -Refer to `C API <./C-API.rst>`__ or the comments in `c\_api.h `__ file, from which the documentation is generated. +Refer to `C API <./C-API.rst>`__ or the comments in `c\_api.h `__ file, from which the documentation is generated. High Level Language Package --------------------------- -See the implementations at `Python-package `__ and `R-package `__. +See the implementations at `Python-package `__ and `R-package `__. Questions --------- Refer to `FAQ <./FAQ.rst>`__. -Also feel free to open `issues `__ if you met problems. +Also feel free to open `issues `__ if you met problems. diff --git a/docs/FAQ.rst b/docs/FAQ.rst index 42cd91868af..e8d07cd0858 100644 --- a/docs/FAQ.rst +++ b/docs/FAQ.rst @@ -16,7 +16,7 @@ LightGBM FAQ Critical ~~~~~~~~ -Please post an issue in `Microsoft/LightGBM repository `__ for any +Please post an issue in `Microsoft/LightGBM repository `__ for any LightGBM issues you encounter. For critical issues (crash, prediction error, nonsense outputs...), you may also ping a member of the core team according to the relevant area of expertise by mentioning them with the arobase (@) symbol: @@ -65,20 +65,20 @@ LightGBM - **Question 3**: When running LightGBM on a large dataset, my computer runs out of RAM. - **Solution 3**: Multiple solutions: set the ``histogram_pool_size`` parameter to the MB you want to use for LightGBM (histogram\_pool\_size + dataset size = approximately RAM used), - lower ``num_leaves`` or lower ``max_bin`` (see `Microsoft/LightGBM#562 `__). + lower ``num_leaves`` or lower ``max_bin`` (see `Microsoft/LightGBM#562 `__). -------------- - **Question 4**: I am using Windows. Should I use Visual Studio or MinGW for compiling LightGBM? -- **Solution 4**: Visual Studio `performs best for LightGBM `__. +- **Solution 4**: Visual Studio `performs best for LightGBM `__. -------------- - **Question 5**: When using LightGBM GPU, I cannot reproduce results over several runs. - **Solution 5**: This is normal and expected behaviour, but you may try to use ``gpu_use_dp = true`` for reproducibility - (see `Microsoft/LightGBM#560 `__). + (see `Microsoft/LightGBM#560 `__). You may also use the CPU version. -------------- @@ -86,7 +86,7 @@ LightGBM - **Question 6**: Bagging is not reproducible when changing the number of threads. - **Solution 6**: LightGBM bagging is multithreaded, so its output depends on the number of threads used. - There is `no workaround currently `__. + There is `no workaround currently `__. -------------- @@ -94,14 +94,14 @@ LightGBM - **Solution 7**: This is expected behaviour for arbitrary parameters. To enable Random Forest, you must use ``bagging_fraction`` and ``feature_fraction`` different from 1, along with a ``bagging_freq``. - `This thread `__ includes an example. + `This thread `__ includes an example. -------------- - **Question 8**: CPU usage is low (like 10%) in Windows when using LightGBM on very large datasets with many-core systems. - **Solution 8**: Please use `Visual Studio `__ - as it may be `10x faster than MinGW `__ especially for very large trees. + as it may be `10x faster than MinGW `__ especially for very large trees. -------------- @@ -115,7 +115,7 @@ LightGBM - **Solution 9**: The column you're trying to pass via ``categorical_feature`` likely contains very large values. Categorical features in LightGBM are limited by int32 range, - so you cannot pass values that are greater than ``Int32.MaxValue`` (2147483647) as categorical features (see `Microsoft/LightGBM#1359 `__). + so you cannot pass values that are greater than ``Int32.MaxValue`` (2147483647) as categorical features (see `Microsoft/LightGBM#1359 `__). You should convert them to integers ranging from zero to the number of categories first. -------------- @@ -145,7 +145,7 @@ LightGBM - **Question 11**: LightGBM hangs when multithreading (OpenMP) and using forking in Linux at the same time. -- **Solution 11**: Use ``nthreads=1`` to disable multithreading of LightGBM. There is a bug with OpenMP which hangs forked sessions with multithreading activated. A more expensive solution is to use new processes instead of using fork, however, keep in mind it is creating new processes where you have to copy memory and load libraries (example: if you want to fork 16 times your current process, then you will require to make 16 copies of your dataset in memory) (see `Microsoft/LightGBM#1789 `__). +- **Solution 11**: Use ``nthreads=1`` to disable multithreading of LightGBM. There is a bug with OpenMP which hangs forked sessions with multithreading activated. A more expensive solution is to use new processes instead of using fork, however, keep in mind it is creating new processes where you have to copy memory and load libraries (example: if you want to fork 16 times your current process, then you will require to make 16 copies of your dataset in memory) (see `Microsoft/LightGBM#1789 `__). An alternative, if multithreading is really necessary inside the forked sessions, would be to compile LightGBM with Intel toolchain. Intel compilers are unaffected by this bug. @@ -160,14 +160,14 @@ R-package - **Solution 1**: Run ``lgb.unloader(wipe = TRUE)`` in the R console, and recreate the LightGBM datasets (this will wipe all LightGBM-related variables). Due to the pointers, choosing to not wipe variables will not fix the error. - This is a known issue: `Microsoft/LightGBM#698 `__. + This is a known issue: `Microsoft/LightGBM#698 `__. -------------- - **Question 2**: I used ``setinfo``, tried to print my ``lgb.Dataset``, and now the R console froze! - **Solution 2**: Avoid printing the ``lgb.Dataset`` after using ``setinfo``. - This is a known bug: `Microsoft/LightGBM#539 `__. + This is a known bug: `Microsoft/LightGBM#539 `__. -------------- @@ -226,9 +226,9 @@ Python-package - **Question 3**: I encounter segmentation faults (segfaults) randomly after installing LightGBM from PyPI using ``pip install lightgbm``. - **Solution 3**: We are doing our best to provide universal wheels which have high running speed and are compatible with any hardware, OS, compiler, etc. at the same time. - However, sometimes it's just impossible to guarantee the possibility of usage of LightGBM in any specific environment (see `Microsoft/LightGBM#1743 `__). + However, sometimes it's just impossible to guarantee the possibility of usage of LightGBM in any specific environment (see `Microsoft/LightGBM#1743 `__). Therefore, the first thing you should try in case of segfaults is **compiling from the source** using ``pip install --no-binary :all: lightgbm``. - For the OS-specific prerequisites see `this guide `__. + For the OS-specific prerequisites see `this guide `__. Also, feel free to post a new issue in our GitHub repository. We always look at each case individually and try to find a root cause. diff --git a/docs/GPU-Performance.rst b/docs/GPU-Performance.rst index f613074eb63..f4f984a2d4e 100644 --- a/docs/GPU-Performance.rst +++ b/docs/GPU-Performance.rst @@ -208,6 +208,6 @@ Huan Zhang, Si Si and Cho-Jui Hsieh. `GPU Acceleration for Large-scale Tree Boos .. _link6: http://stat-computing.org/dataexpo/2009/ -.. _0bb4a82: https://github.com/Microsoft/LightGBM/commit/0bb4a82 +.. _0bb4a82: https://github.com/microsoft/LightGBM/commit/0bb4a82 .. _GPU Acceleration for Large-scale Tree Boosting: https://arxiv.org/abs/1706.08359 diff --git a/docs/GPU-Targets.rst b/docs/GPU-Targets.rst index 96c77d4faff..47e59865507 100644 --- a/docs/GPU-Targets.rst +++ b/docs/GPU-Targets.rst @@ -159,7 +159,7 @@ Known issues: .. _ROCm: https://rocm.github.io/ -.. _our GitHub repo: https://github.com/Microsoft/LightGBM/releases/download/v2.0.12/AMD-APP-SDKInstaller-v3.0.130.136-GA-linux64.tar.bz2 +.. _our GitHub repo: https://github.com/microsoft/LightGBM/releases/download/v2.0.12/AMD-APP-SDKInstaller-v3.0.130.136-GA-linux64.tar.bz2 .. _NVIDIA CUDA Toolkit: https://developer.nvidia.com/cuda-downloads diff --git a/docs/GPU-Tutorial.rst b/docs/GPU-Tutorial.rst index 9da49238eeb..cc302565d1f 100644 --- a/docs/GPU-Tutorial.rst +++ b/docs/GPU-Tutorial.rst @@ -57,7 +57,7 @@ Now we are ready to checkout LightGBM and compile it with GPU support: :: - git clone --recursive https://github.com/Microsoft/LightGBM + git clone --recursive https://github.com/microsoft/LightGBM cd LightGBM mkdir build ; cd build cmake -DUSE_GPU=1 .. @@ -194,7 +194,7 @@ Huan Zhang, Si Si and Cho-Jui Hsieh. "`GPU Acceleration for Large-scale Tree Boo .. _AMDGPU-Pro: https://www.amd.com/en/support -.. _Python-package Examples: https://github.com/Microsoft/LightGBM/tree/master/examples/python-guide +.. _Python-package Examples: https://github.com/microsoft/LightGBM/tree/master/examples/python-guide .. _GPU Acceleration for Large-scale Tree Boosting: https://arxiv.org/abs/1706.08359 diff --git a/docs/GPU-Windows.rst b/docs/GPU-Windows.rst index d4ed6714049..7eee1079a54 100644 --- a/docs/GPU-Windows.rst +++ b/docs/GPU-Windows.rst @@ -257,7 +257,7 @@ Now, we can fetch LightGBM repository for GitHub. Run Git Bash and the following cd C:/ mkdir github_repos cd github_repos - git clone --recursive https://github.com/Microsoft/LightGBM + git clone --recursive https://github.com/microsoft/LightGBM Your LightGBM repository copy should now be under ``C:\github_repos\LightGBM``. You are free to use any folder you want, but you have to adapt. @@ -597,6 +597,6 @@ And open an issue in GitHub `here`_ with that log. .. _CMake: https://cmake.org/download/ -.. _here: https://github.com/Microsoft/LightGBM/issues +.. _here: https://github.com/microsoft/LightGBM/issues .. _GPUCapsViewer: http://www.ozone3d.net/gpu_caps_viewer/ diff --git a/docs/Installation-Guide.rst b/docs/Installation-Guide.rst index a72788010bf..00d38f2cfe8 100644 --- a/docs/Installation-Guide.rst +++ b/docs/Installation-Guide.rst @@ -65,7 +65,7 @@ From Command Line .. code:: - git clone --recursive https://github.com/Microsoft/LightGBM + git clone --recursive https://github.com/microsoft/LightGBM cd LightGBM mkdir build cd build @@ -83,7 +83,7 @@ MinGW-w64 .. code:: - git clone --recursive https://github.com/Microsoft/LightGBM + git clone --recursive https://github.com/microsoft/LightGBM cd LightGBM mkdir build cd build @@ -109,7 +109,7 @@ On Linux LightGBM can be built using **CMake** and **gcc** or **Clang**. .. code:: - git clone --recursive https://github.com/Microsoft/LightGBM ; cd LightGBM + git clone --recursive https://github.com/microsoft/LightGBM ; cd LightGBM mkdir build ; cd build cmake .. make -j4 @@ -144,7 +144,7 @@ Only **Apple Clang** version 8.1 or higher is supported. .. code:: - git clone --recursive https://github.com/Microsoft/LightGBM ; cd LightGBM + git clone --recursive https://github.com/microsoft/LightGBM ; cd LightGBM mkdir build ; cd build # For Mojave (10.14) @@ -180,7 +180,7 @@ gcc .. code:: - git clone --recursive https://github.com/Microsoft/LightGBM ; cd LightGBM + git clone --recursive https://github.com/microsoft/LightGBM ; cd LightGBM export CXX=g++-7 CC=gcc-7 # replace "7" with version of gcc installed on your machine mkdir build ; cd build cmake .. @@ -191,7 +191,7 @@ Also, you may want to read `gcc Tips <./gcc-Tips.rst>`__. Docker ~~~~~~ -Refer to `Docker folder `__. +Refer to `Docker folder `__. Build Threadless Version (not Recommended) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ @@ -241,7 +241,7 @@ From Command Line .. code:: - git clone --recursive https://github.com/Microsoft/LightGBM + git clone --recursive https://github.com/microsoft/LightGBM cd LightGBM mkdir build cd build @@ -259,7 +259,7 @@ MinGW-w64 .. code:: - git clone --recursive https://github.com/Microsoft/LightGBM + git clone --recursive https://github.com/microsoft/LightGBM cd LightGBM mkdir build cd build @@ -281,7 +281,7 @@ On Linux version of LightGBM without OpenMP support can be built using **CMake** .. code:: - git clone --recursive https://github.com/Microsoft/LightGBM ; cd LightGBM + git clone --recursive https://github.com/microsoft/LightGBM ; cd LightGBM mkdir build ; cd build cmake -DUSE_OPENMP=OFF .. make -j4 @@ -308,7 +308,7 @@ Only **Apple Clang** version 8.1 or higher is supported. .. code:: - git clone --recursive https://github.com/Microsoft/LightGBM ; cd LightGBM + git clone --recursive https://github.com/microsoft/LightGBM ; cd LightGBM mkdir build ; cd build cmake -DUSE_OPENMP=OFF .. make -j4 @@ -332,7 +332,7 @@ gcc .. code:: - git clone --recursive https://github.com/Microsoft/LightGBM ; cd LightGBM + git clone --recursive https://github.com/microsoft/LightGBM ; cd LightGBM export CXX=g++-7 CC=gcc-7 # replace "7" with version of gcc installed on your machine mkdir build ; cd build cmake -DUSE_OPENMP=OFF .. @@ -383,7 +383,7 @@ From Command Line .. code:: - git clone --recursive https://github.com/Microsoft/LightGBM + git clone --recursive https://github.com/microsoft/LightGBM cd LightGBM mkdir build cd build @@ -407,7 +407,7 @@ On Linux MPI version of LightGBM can be built using **Open MPI**, **CMake** and .. code:: - git clone --recursive https://github.com/Microsoft/LightGBM ; cd LightGBM + git clone --recursive https://github.com/microsoft/LightGBM ; cd LightGBM mkdir build ; cd build cmake -DUSE_MPI=ON .. make -j4 @@ -446,7 +446,7 @@ Only **Apple Clang** version 8.1 or higher is supported. .. code:: - git clone --recursive https://github.com/Microsoft/LightGBM ; cd LightGBM + git clone --recursive https://github.com/microsoft/LightGBM ; cd LightGBM mkdir build ; cd build # For Mojave (10.14) @@ -489,7 +489,7 @@ gcc .. code:: - git clone --recursive https://github.com/Microsoft/LightGBM ; cd LightGBM + git clone --recursive https://github.com/microsoft/LightGBM ; cd LightGBM export CXX=g++-7 CC=gcc-7 # replace "7" with version of gcc installed on your machine mkdir build ; cd build cmake -DUSE_MPI=ON .. @@ -521,7 +521,7 @@ To build LightGBM GPU version, run the following commands: .. code:: - git clone --recursive https://github.com/Microsoft/LightGBM ; cd LightGBM + git clone --recursive https://github.com/microsoft/LightGBM ; cd LightGBM mkdir build ; cd build cmake -DUSE_GPU=1 .. # if you have installed NVIDIA CUDA to a customized location, you should specify paths to OpenCL headers and library like the following: @@ -563,7 +563,7 @@ Following procedure is for the **MSVC** (Microsoft Visual C++) build. .. code:: - git clone --recursive https://github.com/Microsoft/LightGBM + git clone --recursive https://github.com/microsoft/LightGBM cd LightGBM mkdir build cd build @@ -577,7 +577,7 @@ Following procedure is for the **MSVC** (Microsoft Visual C++) build. Docker ^^^^^^ -Refer to `GPU Docker folder `__. +Refer to `GPU Docker folder `__. Build HDFS Version ~~~~~~~~~~~~~~~~~~ @@ -595,7 +595,7 @@ On Linux HDFS version of LightGBM can be built using **CMake** and **gcc**. .. code:: - git clone --recursive https://github.com/Microsoft/LightGBM ; cd LightGBM + git clone --recursive https://github.com/microsoft/LightGBM ; cd LightGBM mkdir build ; cd build cmake -DUSE_HDFS=ON .. # if you have installed HDFS to a customized location, you should specify paths to HDFS headers (hdfs.h) and library (libhdfs.so) like the following: @@ -627,7 +627,7 @@ VS Build Tools .. code:: - git clone --recursive https://github.com/Microsoft/LightGBM + git clone --recursive https://github.com/microsoft/LightGBM cd LightGBM mkdir build cd build @@ -647,7 +647,7 @@ MinGW-w64 .. code:: - git clone --recursive https://github.com/Microsoft/LightGBM + git clone --recursive https://github.com/microsoft/LightGBM cd LightGBM mkdir build cd build @@ -673,7 +673,7 @@ On Linux Java wrapper of LightGBM can be built using **Java**, **SWIG**, **CMake .. code:: - git clone --recursive https://github.com/Microsoft/LightGBM ; cd LightGBM + git clone --recursive https://github.com/microsoft/LightGBM ; cd LightGBM mkdir build ; cd build cmake -DUSE_SWIG=ON .. make -j4 @@ -707,7 +707,7 @@ Only **Apple Clang** version 8.1 or higher is supported. .. code:: - git clone --recursive https://github.com/Microsoft/LightGBM ; cd LightGBM + git clone --recursive https://github.com/microsoft/LightGBM ; cd LightGBM mkdir build ; cd build # For Mojave (10.14) @@ -745,7 +745,7 @@ gcc .. code:: - git clone --recursive https://github.com/Microsoft/LightGBM ; cd LightGBM + git clone --recursive https://github.com/microsoft/LightGBM ; cd LightGBM export CXX=g++-7 CC=gcc-7 # replace "7" with version of gcc installed on your machine mkdir build ; cd build cmake -DUSE_SWIG=ON -DAPPLE_OUTPUT_DYLIB=ON .. @@ -757,11 +757,11 @@ Also, you may want to read `gcc Tips <./gcc-Tips.rst>`__. .. |download artifacts| image:: ./_static/images/artifacts-not-available.svg :target: https://lightgbm.readthedocs.io/en/latest/Installation-Guide.html -.. _Python-package: https://github.com/Microsoft/LightGBM/tree/master/python-package +.. _Python-package: https://github.com/microsoft/LightGBM/tree/master/python-package -.. _R-package: https://github.com/Microsoft/LightGBM/tree/master/R-package +.. _R-package: https://github.com/microsoft/LightGBM/tree/master/R-package -.. _zip archive: https://github.com/Microsoft/LightGBM/archive/master.zip +.. _zip archive: https://github.com/microsoft/LightGBM/archive/master.zip .. _Visual Studio: https://visualstudio.microsoft.com/downloads/ diff --git a/docs/Key-Events.md b/docs/Key-Events.md index b98fa8ee59c..67b024f60fc 100644 --- a/docs/Key-Events.md +++ b/docs/Key-Events.md @@ -6,120 +6,120 @@ The list includes the commits where the major feature added is considered workin | Date | Commit | Type | Description | | --- | --- | --- | --- | -| 02/09/2017 | [574d780](https://github.com/Microsoft/LightGBM/pull/878) | Docs | Readme Badges (Pull Request 878) | -| 14/08/2017 | [1b8910b](https://github.com/Microsoft/LightGBM/pull/825) | Feature | SHAP Feature Importance (Pull Request 825) | -| 02/08/2017 | [f2bec2b](https://github.com/Microsoft/LightGBM/pull/762) | Feature | Improved categorical feature support (Pull Request 762) | -| 30/07/2017 | [00cb04a](https://github.com/Microsoft/LightGBM/pull/747) | Feature | Better missing value handle (Pull Request 747) | -| 13/07/2017 | [3421bc6](https://github.com/Microsoft/LightGBM/pull/664) | Feature | Automatic Compiler for R-package compilation (Pull Request 664) | -| 10/07/2017 | [ce999b7](https://github.com/Microsoft/LightGBM/pull/678) | Feature | Random Forest mode (Pull Request 678) | -| 22/06/2017 | [d862b3e](https://github.com/Microsoft/LightGBM/pull/642) | CIntegration | Travis OSX Support (Pull Request 642) | -| 20/06/2017 | [80c641c](https://github.com/Microsoft/LightGBM/pull/635) | Release | Python pip package (Pull Request 635) | -| 18/06/2017 | [4d2aa84](https://github.com/Microsoft/LightGBM/pull/634) | CIntegration | AppVeyor Support (Pull Request 634) | -| 06/06/2017 | [2c9ce59](https://github.com/Microsoft/LightGBM/pull/592) | Release | R-package version 0.2 (Pull Request 592) | -| 05/06/2017 | [f98d75f](https://github.com/Microsoft/LightGBM/pull/584) | Feature | Use custom compiler for R-package (Pull Request 584) | -| 29/05/2017 | [993bbd5](https://github.com/Microsoft/LightGBM/pull/559) | Parameter | Early Stopping for predictions (Pull Request 559) | -| 26/05/2017 | [3abff37](https://github.com/Microsoft/LightGBM/commit/3abff370bb353293e4a03e516111dd02785fbd97) | Feature | Parameter to disable missing values (Commit) | -| 21/05/2017 | [4cf9376](https://github.com/Microsoft/LightGBM/commit/4cf9376d6652d3d7afa82e98dfb363af9275969d) | Feature | Limitation of threads for dataset construction (Commit) | -| 15/05/2017 | [e984b0d](https://github.com/Microsoft/LightGBM/pull/516) | Feature | Support for missing values (Pull Request 516) | -| 14/05/2017 | [358553d](https://github.com/Microsoft/LightGBM/pull/511) | Docs | Interactive External Website (Pull Request 511) | -| 04/05/2017 | [ca30b8c](https://github.com/Microsoft/LightGBM/pull/489) | Docs | Read The Docs (Pull Request 489) | -| 28/04/2017 | [8a19834](https://github.com/Microsoft/LightGBM/pull/469) | Feature | If-Then-Else C++ Trees Generation (Pull Request 469) | -| 18/04/2017 | [7339ed6](https://github.com/Microsoft/LightGBM/pull/426) | Feature | Whitespaces Removed from Features support (Pull Request 426) | -| 14/04/2017 | [9224a9d](https://github.com/Microsoft/LightGBM/pull/415) | Release | GPU support (Pull Request 415)
With original ([0bb4a82](https://github.com/Microsoft/LightGBM/pull/368) on 09/04/2017, Pull Request 368) | -| 13/04/2017 | [ab55910](https://github.com/Microsoft/LightGBM/pull/404) | Feature | Speed Improvements for Prediction (Pull Request 404) | -| 06/04/2017 | [bfb0217](https://github.com/Microsoft/LightGBM/pull/383) | Feature | Objective Transformations to the Objective (Pull Request 383) | -| 05/04/2017 | [d4c4d9a](https://github.com/Microsoft/LightGBM/pull/381) | Feature | Regression Speed Improvements (Pull Request 381) | -| 03/04/2017 | [b6c973a](https://github.com/Microsoft/LightGBM/pull/378) | Feature | Unloading Memory Fix support for R-package (Pull Request 378) | -| 17/03/2017 | [06a915a](https://github.com/Microsoft/LightGBM/pull/347) | Feature | RDS support for R pacakge (Pull Request 347) | -| 10/03/2017 | [b7e5f07](https://github.com/Microsoft/LightGBM/pull/340) | Feature | Support Self-Contained R-package (Pull Request 340) | -| 02/03/2017 | [4d6ff28](https://github.com/Microsoft/LightGBM/pull/330) | Feature | Feature Contribution Plot for R-package (Pull Request 330) | -| 01/03/2017 | [166421e](https://github.com/Microsoft/LightGBM/pull/328) | Feature | Feature Importance Plot for R-package (Pull Request 328) | -| 27/02/2017 | [fddb52f](https://github.com/Microsoft/LightGBM/pull/323) | Feature | Feature Contribution for R-package (Pull Request 323) | -| 20/02/2017 | [10212b5](https://github.com/Microsoft/LightGBM/pull/300) | Release | v2 (Pull Request 300) | -| 12/02/2017 | [ea6bc0a](https://github.com/Microsoft/LightGBM/pull/290) | Release | v1 (Pull Request 290) | -| 02/02/2017 | [8c8ed6c](https://github.com/Microsoft/LightGBM/pull/275) | Feature | Docker support (Pull Request 275) | -| 30/01/2017 | [4f3e9d8](https://github.com/Microsoft/LightGBM/pull/270) | Feature | Poisson Objective support (Pull Request 270) | -| 28/01/2017 | [5856554](https://github.com/Microsoft/LightGBM/pull/266) | Feature | Plot Metric support for Python-package (Pull Request 266) | -| 25/01/2017 | [8980fc7](https://github.com/Microsoft/LightGBM/pull/262) | Feature | Plot Tree support for Python-package (Pull Request 262)
With original ([fafbcb3](https://github.com/Microsoft/LightGBM/pull/258) on 25/01/2017, Pull Request 258) | -| 20/01/2017 | [abaefb5](https://github.com/Microsoft/LightGBM/pull/237) | Feature | Feature Importance Plot for Python-package (Pull Request 237) | -| 16/01/2017 | [a2ae838](https://github.com/Microsoft/LightGBM/pull/229) | Feature | Categorical Feature support for R-package (Pull Request 229) | -| 16/01/2017 | [57d5527](https://github.com/Microsoft/LightGBM/pull/218) | Feature | Pandas Categorical support for Python-package (Pull Request 193)
With original ([a2ae838](https://github.com/Microsoft/LightGBM/pull/193) on 12/01/2017, Pull Request 193) | -| 10/01/2017 | [fb732c3](https://github.com/Microsoft/LightGBM/pull/180) | Feature | Fair Loss Objective support (Pull Request 180) | -| 09/01/2017 | [27d3eb3](https://github.com/Microsoft/LightGBM/pull/178) | Feature | Huber Loss Objective support (Pull Request 178)
With original ([a87af87](https://github.com/Microsoft/LightGBM/pull/174) on 09/01/2017, Pull Request 174) | -| 09/01/2017 | [9b2558d](https://github.com/Microsoft/LightGBM/pull/177) | Feature | devtools R Installation support (Pull Request 177) | -| 09/01/2017 | [6219df7](https://github.com/Microsoft/LightGBM/pull/175) | Feature | L1 Loss Objective support (Pull Request 175) | -| 08/01/2017 | [551d59c](https://github.com/Microsoft/LightGBM/pull/168) | Release | R support (Pull Request 168) | -| 05/01/2017 | [96d08f4](https://github.com/Microsoft/LightGBM/pull/153) | Feature | PMML support (Pull Request 153) | -| 01/01/2017 | [a034cee](https://github.com/Microsoft/LightGBM/pull/151) | Feature | Pickle support for Python-package (Pull Request 151) | -| 26/12/2016 | [96cba41](https://github.com/Microsoft/LightGBM/pull/139) | Parameter | DART xgboost support (Pull Request 139) | -| 19/12/2016 | [99b483d](https://github.com/Microsoft/LightGBM/pull/133) | Parameter | Learning Rate in DART support (Pull Request 133) | -| 01/12/2016 | [16d1853](https://github.com/Microsoft/LightGBM/pull/94) | Release | Python support (Pull Request 94) | -| 11/11/2016 | [98be7e3](https://github.com/Microsoft/LightGBM/pull/67) | Feature | DART booster support (Pull Request 67) | -| 08/11/2016 | [785398a](https://github.com/Microsoft/LightGBM/pull/69) | Parameter | L1 Regularization, L2 Regularization, Minimum Gain to Split support (Pull Request 69) | -| 05/11/2016 | [1466f90](https://github.com/Microsoft/LightGBM/pull/108) | Release | Categorical Feature support (Pull Request 108) | -| 01/11/2016 | [aa796a8](https://github.com/Microsoft/LightGBM/pull/53) | Feature | Multiclass classification support (Pull Request 53) | -| 28/10/2016 | [c45d1d9](https://github.com/Microsoft/LightGBM/pull/42) | Feature | Feature Importance support (Pull Request 42) | -| 25/10/2016 | [a6a75fe](https://github.com/Microsoft/LightGBM/pull/35) | Parameter | Maximum Depth support (Pull Request 35) | -| 24/10/2016 | [9fe0dea](https://github.com/Microsoft/LightGBM/pull/30) | Parameter | Leaf Index Prediction support (Pull Request 30) | -| 21/10/2016 | [7aaba32](https://github.com/Microsoft/LightGBM/pull/27) | Parameter | Early Stopping support (Pull Request 27)
With original ([7d4b6d4](https://github.com/Microsoft/LightGBM/pull/21) on 20/10/2017, Pull Request 21) | +| 02/09/2017 | [574d780](https://github.com/microsoft/LightGBM/pull/878) | Docs | Readme Badges (Pull Request 878) | +| 14/08/2017 | [1b8910b](https://github.com/microsoft/LightGBM/pull/825) | Feature | SHAP Feature Importance (Pull Request 825) | +| 02/08/2017 | [f2bec2b](https://github.com/microsoft/LightGBM/pull/762) | Feature | Improved categorical feature support (Pull Request 762) | +| 30/07/2017 | [00cb04a](https://github.com/microsoft/LightGBM/pull/747) | Feature | Better missing value handle (Pull Request 747) | +| 13/07/2017 | [3421bc6](https://github.com/microsoft/LightGBM/pull/664) | Feature | Automatic Compiler for R-package compilation (Pull Request 664) | +| 10/07/2017 | [ce999b7](https://github.com/microsoft/LightGBM/pull/678) | Feature | Random Forest mode (Pull Request 678) | +| 22/06/2017 | [d862b3e](https://github.com/microsoft/LightGBM/pull/642) | CIntegration | Travis OSX Support (Pull Request 642) | +| 20/06/2017 | [80c641c](https://github.com/microsoft/LightGBM/pull/635) | Release | Python pip package (Pull Request 635) | +| 18/06/2017 | [4d2aa84](https://github.com/microsoft/LightGBM/pull/634) | CIntegration | AppVeyor Support (Pull Request 634) | +| 06/06/2017 | [2c9ce59](https://github.com/microsoft/LightGBM/pull/592) | Release | R-package version 0.2 (Pull Request 592) | +| 05/06/2017 | [f98d75f](https://github.com/microsoft/LightGBM/pull/584) | Feature | Use custom compiler for R-package (Pull Request 584) | +| 29/05/2017 | [993bbd5](https://github.com/microsoft/LightGBM/pull/559) | Parameter | Early Stopping for predictions (Pull Request 559) | +| 26/05/2017 | [3abff37](https://github.com/microsoft/LightGBM/commit/3abff370bb353293e4a03e516111dd02785fbd97) | Feature | Parameter to disable missing values (Commit) | +| 21/05/2017 | [4cf9376](https://github.com/microsoft/LightGBM/commit/4cf9376d6652d3d7afa82e98dfb363af9275969d) | Feature | Limitation of threads for dataset construction (Commit) | +| 15/05/2017 | [e984b0d](https://github.com/microsoft/LightGBM/pull/516) | Feature | Support for missing values (Pull Request 516) | +| 14/05/2017 | [358553d](https://github.com/microsoft/LightGBM/pull/511) | Docs | Interactive External Website (Pull Request 511) | +| 04/05/2017 | [ca30b8c](https://github.com/microsoft/LightGBM/pull/489) | Docs | Read The Docs (Pull Request 489) | +| 28/04/2017 | [8a19834](https://github.com/microsoft/LightGBM/pull/469) | Feature | If-Then-Else C++ Trees Generation (Pull Request 469) | +| 18/04/2017 | [7339ed6](https://github.com/microsoft/LightGBM/pull/426) | Feature | Whitespaces Removed from Features support (Pull Request 426) | +| 14/04/2017 | [9224a9d](https://github.com/microsoft/LightGBM/pull/415) | Release | GPU support (Pull Request 415)
With original ([0bb4a82](https://github.com/microsoft/LightGBM/pull/368) on 09/04/2017, Pull Request 368) | +| 13/04/2017 | [ab55910](https://github.com/microsoft/LightGBM/pull/404) | Feature | Speed Improvements for Prediction (Pull Request 404) | +| 06/04/2017 | [bfb0217](https://github.com/microsoft/LightGBM/pull/383) | Feature | Objective Transformations to the Objective (Pull Request 383) | +| 05/04/2017 | [d4c4d9a](https://github.com/microsoft/LightGBM/pull/381) | Feature | Regression Speed Improvements (Pull Request 381) | +| 03/04/2017 | [b6c973a](https://github.com/microsoft/LightGBM/pull/378) | Feature | Unloading Memory Fix support for R-package (Pull Request 378) | +| 17/03/2017 | [06a915a](https://github.com/microsoft/LightGBM/pull/347) | Feature | RDS support for R pacakge (Pull Request 347) | +| 10/03/2017 | [b7e5f07](https://github.com/microsoft/LightGBM/pull/340) | Feature | Support Self-Contained R-package (Pull Request 340) | +| 02/03/2017 | [4d6ff28](https://github.com/microsoft/LightGBM/pull/330) | Feature | Feature Contribution Plot for R-package (Pull Request 330) | +| 01/03/2017 | [166421e](https://github.com/microsoft/LightGBM/pull/328) | Feature | Feature Importance Plot for R-package (Pull Request 328) | +| 27/02/2017 | [fddb52f](https://github.com/microsoft/LightGBM/pull/323) | Feature | Feature Contribution for R-package (Pull Request 323) | +| 20/02/2017 | [10212b5](https://github.com/microsoft/LightGBM/pull/300) | Release | v2 (Pull Request 300) | +| 12/02/2017 | [ea6bc0a](https://github.com/microsoft/LightGBM/pull/290) | Release | v1 (Pull Request 290) | +| 02/02/2017 | [8c8ed6c](https://github.com/microsoft/LightGBM/pull/275) | Feature | Docker support (Pull Request 275) | +| 30/01/2017 | [4f3e9d8](https://github.com/microsoft/LightGBM/pull/270) | Feature | Poisson Objective support (Pull Request 270) | +| 28/01/2017 | [5856554](https://github.com/microsoft/LightGBM/pull/266) | Feature | Plot Metric support for Python-package (Pull Request 266) | +| 25/01/2017 | [8980fc7](https://github.com/microsoft/LightGBM/pull/262) | Feature | Plot Tree support for Python-package (Pull Request 262)
With original ([fafbcb3](https://github.com/microsoft/LightGBM/pull/258) on 25/01/2017, Pull Request 258) | +| 20/01/2017 | [abaefb5](https://github.com/microsoft/LightGBM/pull/237) | Feature | Feature Importance Plot for Python-package (Pull Request 237) | +| 16/01/2017 | [a2ae838](https://github.com/microsoft/LightGBM/pull/229) | Feature | Categorical Feature support for R-package (Pull Request 229) | +| 16/01/2017 | [57d5527](https://github.com/microsoft/LightGBM/pull/218) | Feature | Pandas Categorical support for Python-package (Pull Request 193)
With original ([a2ae838](https://github.com/microsoft/LightGBM/pull/193) on 12/01/2017, Pull Request 193) | +| 10/01/2017 | [fb732c3](https://github.com/microsoft/LightGBM/pull/180) | Feature | Fair Loss Objective support (Pull Request 180) | +| 09/01/2017 | [27d3eb3](https://github.com/microsoft/LightGBM/pull/178) | Feature | Huber Loss Objective support (Pull Request 178)
With original ([a87af87](https://github.com/microsoft/LightGBM/pull/174) on 09/01/2017, Pull Request 174) | +| 09/01/2017 | [9b2558d](https://github.com/microsoft/LightGBM/pull/177) | Feature | devtools R Installation support (Pull Request 177) | +| 09/01/2017 | [6219df7](https://github.com/microsoft/LightGBM/pull/175) | Feature | L1 Loss Objective support (Pull Request 175) | +| 08/01/2017 | [551d59c](https://github.com/microsoft/LightGBM/pull/168) | Release | R support (Pull Request 168) | +| 05/01/2017 | [96d08f4](https://github.com/microsoft/LightGBM/pull/153) | Feature | PMML support (Pull Request 153) | +| 01/01/2017 | [a034cee](https://github.com/microsoft/LightGBM/pull/151) | Feature | Pickle support for Python-package (Pull Request 151) | +| 26/12/2016 | [96cba41](https://github.com/microsoft/LightGBM/pull/139) | Parameter | DART xgboost support (Pull Request 139) | +| 19/12/2016 | [99b483d](https://github.com/microsoft/LightGBM/pull/133) | Parameter | Learning Rate in DART support (Pull Request 133) | +| 01/12/2016 | [16d1853](https://github.com/microsoft/LightGBM/pull/94) | Release | Python support (Pull Request 94) | +| 11/11/2016 | [98be7e3](https://github.com/microsoft/LightGBM/pull/67) | Feature | DART booster support (Pull Request 67) | +| 08/11/2016 | [785398a](https://github.com/microsoft/LightGBM/pull/69) | Parameter | L1 Regularization, L2 Regularization, Minimum Gain to Split support (Pull Request 69) | +| 05/11/2016 | [1466f90](https://github.com/microsoft/LightGBM/pull/108) | Release | Categorical Feature support (Pull Request 108) | +| 01/11/2016 | [aa796a8](https://github.com/microsoft/LightGBM/pull/53) | Feature | Multiclass classification support (Pull Request 53) | +| 28/10/2016 | [c45d1d9](https://github.com/microsoft/LightGBM/pull/42) | Feature | Feature Importance support (Pull Request 42) | +| 25/10/2016 | [a6a75fe](https://github.com/microsoft/LightGBM/pull/35) | Parameter | Maximum Depth support (Pull Request 35) | +| 24/10/2016 | [9fe0dea](https://github.com/microsoft/LightGBM/pull/30) | Parameter | Leaf Index Prediction support (Pull Request 30) | +| 21/10/2016 | [7aaba32](https://github.com/microsoft/LightGBM/pull/27) | Parameter | Early Stopping support (Pull Request 27)
With original ([7d4b6d4](https://github.com/microsoft/LightGBM/pull/21) on 20/10/2017, Pull Request 21) | | 17/10/2016 | [65ddd85](https://github.com/guFalcon/LightGBM/commit/65ddd852d8d160d86080c45512bd435d15837927) | Release | LightGBM compilable (Commit) | ## Modification List -* 02/09/2017 [Microsoft/LightGBM@574d780](https://github.com/Microsoft/LightGBM/pull/878): Docs: Readme Badges (Pull Request 878) -* 14/08/2017 [Microsoft/LightGBM@1b8910b](https://github.com/Microsoft/LightGBM/pull/825): Feature: SHAP Feature Importance (Pull Request 825) -* 02/08/2017 [Microsoft/LightGBM@f2bec2b](https://github.com/Microsoft/LightGBM/pull/762): Feature: Improved categorical feature support (Pull Request 762) -* 30/07/2017 [Microsoft/LightGBM@00cb04a](https://github.com/Microsoft/LightGBM/pull/747): Feature: Better missing value handle (Pull Request 747) -* 13/07/2017 [Microsoft/LightGBM@3421bc6](https://github.com/Microsoft/LightGBM/pull/664): Feature: Automatic Compiler for R-package compilation (Pull Request 664) -* 10/07/2017 [Microsoft/LightGBM@ce999b7](https://github.com/Microsoft/LightGBM/pull/678): Feature: Random Forest mode (Pull Request 678) -* 22/06/2017 [Microsoft/LightGBM@d862b3e](https://github.com/Microsoft/LightGBM/pull/642): CIntegration: Travis OSX Support (Pull Request 642) -* 20/06/2017 [Microsoft/LightGBM@80c641c](https://github.com/Microsoft/LightGBM/pull/635): Release: Python pip package (Pull Request 635) -* 18/06/2017 [Microsoft/LightGBM@4d2aa84](https://github.com/Microsoft/LightGBM/pull/634): CIntegration: AppVeyor Support (Pull Request 634) -* 06/06/2017 [Microsoft/LightGBM@2c9ce59](https://github.com/Microsoft/LightGBM/pull/592): Release: R-package version 0.2 (Pull Request 592) -* 05/06/2017 [Microsoft/LightGBM@f98d75f](https://github.com/Microsoft/LightGBM/pull/584): Feature: Use custom compiler for R-package (Pull Request 584) -* 29/05/2017 [Microsoft/LightGBM@993bbd5](https://github.com/Microsoft/LightGBM/pull/559): Parameter: Early Stopping for predictions (Pull Request 559) -* 26/05/2017 [Microsoft/LightGBM@3abff37](https://github.com/Microsoft/LightGBM/commit/3abff370bb353293e4a03e516111dd02785fbd97): Feature: Parameter to disable missing values (Commit) -* 21/05/2017 [Microsoft/LightGBM@4cf9376](https://github.com/Microsoft/LightGBM/commit/4cf9376d6652d3d7afa82e98dfb363af9275969d): Feature: Limitation of threads for dataset construction (Commit) -* 15/05/2017 [Microsoft/LightGBM@e984b0d](https://github.com/Microsoft/LightGBM/pull/516): Feature: Support for missing values (Pull Request 516) -* 14/05/2017 [Microsoft/LightGBM@358553d](https://github.com/Microsoft/LightGBM/pull/511): Docs: Interactive External Website (Pull Request 511) -* 04/05/2017 [Microsoft/LightGBM@ca30b8c](https://github.com/Microsoft/LightGBM/pull/489): Docs: Read The Docs (Pull Request 489) -* 28/04/2017 [Microsoft/LightGBM@8a19834](https://github.com/Microsoft/LightGBM/pull/469): Feature: If-Then-Else C++ Trees Generation (Pull Request 469) -* 18/04/2017 ([Microsoft/LightGBM@7339ed6](https://github.com/Microsoft/LightGBM/pull/426)): Feature: Whitespaces Removed from Features support (Pull Request 426) -* 14/04/2017 ([Microsoft/LightGBM@9224a9d](https://github.com/Microsoft/LightGBM/pull/415)): Release: GPU support (Pull Request 415) with original ([Microsoft/LightGBM@0bb4a82](https://github.com/Microsoft/LightGBM/pull/368) on 09/04/2017, Pull Request 368) -* 13/04/2017 ([Microsoft/LightGBM@ab55910](https://github.com/Microsoft/LightGBM/pull/404)): Feature: Speed Improvements for Prediction (Pull Request 404) -* 06/04/2017 ([Microsoft/LightGBM@bfb0217](https://github.com/Microsoft/LightGBM/pull/383)): Feature: Objective Transformations to the Objective (Pull Request 383) -* 05/04/2017 ([Microsoft/LightGBM@d4c4d9a](https://github.com/Microsoft/LightGBM/pull/381)): Feature: Regression Speed Improvements (Pull Request 381) -* 03/04/2017 ([Microsoft/LightGBM@b6c973a](https://github.com/Microsoft/LightGBM/pull/378)): Feature: Unloading Memory Fix support for R-package (Pull Request 378) -* 17/03/2017 ([Microsoft/LightGBM@06a915a](https://github.com/Microsoft/LightGBM/pull/347)): Feature: RDS support for R pacakge (Pull Request 347) -* 10/03/2017 ([Microsoft/LightGBM@b7e5f07](https://github.com/Microsoft/LightGBM/pull/340)): Feature: Support Self-Contained R-package (Pull Request 340) -* 02/03/2017 ([Microsoft/LightGBM@4d6ff28](https://github.com/Microsoft/LightGBM/pull/330)): Feature: Feature Contribution Plot for R-package (Pull Request 330) -* 01/03/2017 ([Microsoft/LightGBM@166421e](https://github.com/Microsoft/LightGBM/pull/328)): Feature: Feature Importance Plot for R-package (Pull Request 328) -* 27/02/2017 ([Microsoft/LightGBM@fddb52f](https://github.com/Microsoft/LightGBM/pull/323)): Feature: Feature Contribution for R-package (Pull Request 323) -* 20/02/2017 ([Microsoft/LightGBM@10212b5](https://github.com/Microsoft/LightGBM/pull/300)): Release: v2 (Pull Request 300) -* 12/02/2017 ([Microsoft/LightGBM@ea6bc0a](https://github.com/Microsoft/LightGBM/pull/290)): Release: v1 (Pull Request 290) -* 02/02/2017 ([Microsoft/LightGBM@8c8ed6c](https://github.com/Microsoft/LightGBM/pull/275)): Feature: Docker support (Pull Request 275) -* 30/01/2017 ([Microsoft/LightGBM@4f3e9d8](https://github.com/Microsoft/LightGBM/pull/270)): Feature: Poisson Objective support (Pull Request 270) -* 28/01/2017 ([Microsoft/LightGBM@5856554](https://github.com/Microsoft/LightGBM/pull/266)): Feature: Plot Metric support for Python-package (Pull Request 266) -* 25/01/2017 ([Microsoft/LightGBM@8980fc7](https://github.com/Microsoft/LightGBM/pull/262)): Feature: Plot Tree support for Python-package (Pull Request 262) with original ([Microsoft/LightGBM@fafbcb3](https://github.com/Microsoft/LightGBM/pull/258) on 25/01/2017, Pull Request 258) -* 20/01/2017 ([Microsoft/LightGBM@abaefb5](https://github.com/Microsoft/LightGBM/pull/237)): Feature: Feature Importance Plot for Python-package (Pull Request 237) -* 16/01/2017 ([Microsoft/LightGBM@a2ae838](https://github.com/Microsoft/LightGBM/pull/229)): Feature: Categorical Feature support for R-package (Pull Request 229) -* 16/01/2017 ([Microsoft/LightGBM@57d5527](https://github.com/Microsoft/LightGBM/pull/218)): Feature: Pandas Categorical support for Python-package (Pull Request 193) with original ([Microsoft/LightGBM@a2ae838](https://github.com/Microsoft/LightGBM/pull/193) on 12/01/2017, Pull Request 193) -* 10/01/2017 ([Microsoft/LightGBM@fb732c3](https://github.com/Microsoft/LightGBM/pull/180)): Feature: Fair Loss Objective support (Pull Request 180) -* 09/01/2017 ([Microsoft/LightGBM@27d3eb3](https://github.com/Microsoft/LightGBM/pull/178)): Feature: Huber Loss Objective support (Pull Request 178) with original ([Microsoft/LightGBM@a87af87](https://github.com/Microsoft/LightGBM/pull/174) on 09/01/2017, Pull Request 174) -* 09/01/2017 ([Microsoft/LightGBM@9b2558d](https://github.com/Microsoft/LightGBM/pull/177)): Feature: devtools R Installation support (Pull Request 177) -* 09/01/2017 ([Microsoft/LightGBM@6219df7](https://github.com/Microsoft/LightGBM/pull/175)): Feature: L1 Loss Objective support (Pull Request 175) -* 08/01/2017 ([Microsoft/LightGBM@551d59c](https://github.com/Microsoft/LightGBM/pull/168)): Release: R support (Pull Request 168) -* 05/01/2017 ([Microsoft/LightGBM@96d08f4](https://github.com/Microsoft/LightGBM/pull/153)): Feature: PMML support (Pull Request 153) -* 01/01/2017 ([Microsoft/LightGBM@a034cee](https://github.com/Microsoft/LightGBM/pull/151)): Feature: Pickle support for Python-package (Pull Request 151) -* 26/12/2016 ([Microsoft/LightGBM@96cba41](https://github.com/Microsoft/LightGBM/pull/139)): Parameter: DART xgboost support (Pull Request 139) -* 19/12/2016 ([Microsoft/LightGBM@99b483d](https://github.com/Microsoft/LightGBM/pull/133)): Parameter: Learning Rate in DART support (Pull Request 133) -* 01/12/2016 ([Microsoft/LightGBM@16d1853](https://github.com/Microsoft/LightGBM/pull/94)): Release: Python support (Pull Request 94) -* 11/11/2016 ([Microsoft/LightGBM@98be7e3](https://github.com/Microsoft/LightGBM/pull/67)): Feature: DART booster support (Pull Request 67) -* 08/11/2016 ([Microsoft/LightGBM@785398a](https://github.com/Microsoft/LightGBM/pull/69)): Parameter: L1 Regularization, L2 Regularization, Minimum Gain to Split support (Pull Request 69) -* 05/11/2016 ([Microsoft/LightGBM@1466f90](https://github.com/Microsoft/LightGBM/pull/108)): Release: Categorical Feature support (Pull Request 108) -* 01/11/2016 ([Microsoft/LightGBM@aa796a8](https://github.com/Microsoft/LightGBM/pull/53)): Feature: Multiclass classification support (Pull Request 53) -* 28/10/2016 ([Microsoft/LightGBM@c45d1d9](https://github.com/Microsoft/LightGBM/pull/42)): Feature: Feature Importance support (Pull Request 42) -* 25/10/2016 ([Microsoft/LightGBM@a6a75fe](https://github.com/Microsoft/LightGBM/pull/35)): Parameter: Maximum Depth support (Pull Request 35) -* 24/10/2016 ([Microsoft/LightGBM@9fe0dea](https://github.com/Microsoft/LightGBM/pull/30)): Parameter: Leaf Index Prediction support (Pull Request 30) -* 21/10/2016 ([Microsoft/LightGBM@7aaba32](https://github.com/Microsoft/LightGBM/pull/27)): Parameter: Early Stopping support (Pull Request 27) with original ([Microsoft/LightGBM@7d4b6d4](https://github.com/Microsoft/LightGBM/pull/21) on 20/10/2017, Pull Request 21) +* 02/09/2017 [Microsoft/LightGBM@574d780](https://github.com/microsoft/LightGBM/pull/878): Docs: Readme Badges (Pull Request 878) +* 14/08/2017 [Microsoft/LightGBM@1b8910b](https://github.com/microsoft/LightGBM/pull/825): Feature: SHAP Feature Importance (Pull Request 825) +* 02/08/2017 [Microsoft/LightGBM@f2bec2b](https://github.com/microsoft/LightGBM/pull/762): Feature: Improved categorical feature support (Pull Request 762) +* 30/07/2017 [Microsoft/LightGBM@00cb04a](https://github.com/microsoft/LightGBM/pull/747): Feature: Better missing value handle (Pull Request 747) +* 13/07/2017 [Microsoft/LightGBM@3421bc6](https://github.com/microsoft/LightGBM/pull/664): Feature: Automatic Compiler for R-package compilation (Pull Request 664) +* 10/07/2017 [Microsoft/LightGBM@ce999b7](https://github.com/microsoft/LightGBM/pull/678): Feature: Random Forest mode (Pull Request 678) +* 22/06/2017 [Microsoft/LightGBM@d862b3e](https://github.com/microsoft/LightGBM/pull/642): CIntegration: Travis OSX Support (Pull Request 642) +* 20/06/2017 [Microsoft/LightGBM@80c641c](https://github.com/microsoft/LightGBM/pull/635): Release: Python pip package (Pull Request 635) +* 18/06/2017 [Microsoft/LightGBM@4d2aa84](https://github.com/microsoft/LightGBM/pull/634): CIntegration: AppVeyor Support (Pull Request 634) +* 06/06/2017 [Microsoft/LightGBM@2c9ce59](https://github.com/microsoft/LightGBM/pull/592): Release: R-package version 0.2 (Pull Request 592) +* 05/06/2017 [Microsoft/LightGBM@f98d75f](https://github.com/microsoft/LightGBM/pull/584): Feature: Use custom compiler for R-package (Pull Request 584) +* 29/05/2017 [Microsoft/LightGBM@993bbd5](https://github.com/microsoft/LightGBM/pull/559): Parameter: Early Stopping for predictions (Pull Request 559) +* 26/05/2017 [Microsoft/LightGBM@3abff37](https://github.com/microsoft/LightGBM/commit/3abff370bb353293e4a03e516111dd02785fbd97): Feature: Parameter to disable missing values (Commit) +* 21/05/2017 [Microsoft/LightGBM@4cf9376](https://github.com/microsoft/LightGBM/commit/4cf9376d6652d3d7afa82e98dfb363af9275969d): Feature: Limitation of threads for dataset construction (Commit) +* 15/05/2017 [Microsoft/LightGBM@e984b0d](https://github.com/microsoft/LightGBM/pull/516): Feature: Support for missing values (Pull Request 516) +* 14/05/2017 [Microsoft/LightGBM@358553d](https://github.com/microsoft/LightGBM/pull/511): Docs: Interactive External Website (Pull Request 511) +* 04/05/2017 [Microsoft/LightGBM@ca30b8c](https://github.com/microsoft/LightGBM/pull/489): Docs: Read The Docs (Pull Request 489) +* 28/04/2017 [Microsoft/LightGBM@8a19834](https://github.com/microsoft/LightGBM/pull/469): Feature: If-Then-Else C++ Trees Generation (Pull Request 469) +* 18/04/2017 ([Microsoft/LightGBM@7339ed6](https://github.com/microsoft/LightGBM/pull/426)): Feature: Whitespaces Removed from Features support (Pull Request 426) +* 14/04/2017 ([Microsoft/LightGBM@9224a9d](https://github.com/microsoft/LightGBM/pull/415)): Release: GPU support (Pull Request 415) with original ([Microsoft/LightGBM@0bb4a82](https://github.com/microsoft/LightGBM/pull/368) on 09/04/2017, Pull Request 368) +* 13/04/2017 ([Microsoft/LightGBM@ab55910](https://github.com/microsoft/LightGBM/pull/404)): Feature: Speed Improvements for Prediction (Pull Request 404) +* 06/04/2017 ([Microsoft/LightGBM@bfb0217](https://github.com/microsoft/LightGBM/pull/383)): Feature: Objective Transformations to the Objective (Pull Request 383) +* 05/04/2017 ([Microsoft/LightGBM@d4c4d9a](https://github.com/microsoft/LightGBM/pull/381)): Feature: Regression Speed Improvements (Pull Request 381) +* 03/04/2017 ([Microsoft/LightGBM@b6c973a](https://github.com/microsoft/LightGBM/pull/378)): Feature: Unloading Memory Fix support for R-package (Pull Request 378) +* 17/03/2017 ([Microsoft/LightGBM@06a915a](https://github.com/microsoft/LightGBM/pull/347)): Feature: RDS support for R pacakge (Pull Request 347) +* 10/03/2017 ([Microsoft/LightGBM@b7e5f07](https://github.com/microsoft/LightGBM/pull/340)): Feature: Support Self-Contained R-package (Pull Request 340) +* 02/03/2017 ([Microsoft/LightGBM@4d6ff28](https://github.com/microsoft/LightGBM/pull/330)): Feature: Feature Contribution Plot for R-package (Pull Request 330) +* 01/03/2017 ([Microsoft/LightGBM@166421e](https://github.com/microsoft/LightGBM/pull/328)): Feature: Feature Importance Plot for R-package (Pull Request 328) +* 27/02/2017 ([Microsoft/LightGBM@fddb52f](https://github.com/microsoft/LightGBM/pull/323)): Feature: Feature Contribution for R-package (Pull Request 323) +* 20/02/2017 ([Microsoft/LightGBM@10212b5](https://github.com/microsoft/LightGBM/pull/300)): Release: v2 (Pull Request 300) +* 12/02/2017 ([Microsoft/LightGBM@ea6bc0a](https://github.com/microsoft/LightGBM/pull/290)): Release: v1 (Pull Request 290) +* 02/02/2017 ([Microsoft/LightGBM@8c8ed6c](https://github.com/microsoft/LightGBM/pull/275)): Feature: Docker support (Pull Request 275) +* 30/01/2017 ([Microsoft/LightGBM@4f3e9d8](https://github.com/microsoft/LightGBM/pull/270)): Feature: Poisson Objective support (Pull Request 270) +* 28/01/2017 ([Microsoft/LightGBM@5856554](https://github.com/microsoft/LightGBM/pull/266)): Feature: Plot Metric support for Python-package (Pull Request 266) +* 25/01/2017 ([Microsoft/LightGBM@8980fc7](https://github.com/microsoft/LightGBM/pull/262)): Feature: Plot Tree support for Python-package (Pull Request 262) with original ([Microsoft/LightGBM@fafbcb3](https://github.com/microsoft/LightGBM/pull/258) on 25/01/2017, Pull Request 258) +* 20/01/2017 ([Microsoft/LightGBM@abaefb5](https://github.com/microsoft/LightGBM/pull/237)): Feature: Feature Importance Plot for Python-package (Pull Request 237) +* 16/01/2017 ([Microsoft/LightGBM@a2ae838](https://github.com/microsoft/LightGBM/pull/229)): Feature: Categorical Feature support for R-package (Pull Request 229) +* 16/01/2017 ([Microsoft/LightGBM@57d5527](https://github.com/microsoft/LightGBM/pull/218)): Feature: Pandas Categorical support for Python-package (Pull Request 193) with original ([Microsoft/LightGBM@a2ae838](https://github.com/microsoft/LightGBM/pull/193) on 12/01/2017, Pull Request 193) +* 10/01/2017 ([Microsoft/LightGBM@fb732c3](https://github.com/microsoft/LightGBM/pull/180)): Feature: Fair Loss Objective support (Pull Request 180) +* 09/01/2017 ([Microsoft/LightGBM@27d3eb3](https://github.com/microsoft/LightGBM/pull/178)): Feature: Huber Loss Objective support (Pull Request 178) with original ([Microsoft/LightGBM@a87af87](https://github.com/microsoft/LightGBM/pull/174) on 09/01/2017, Pull Request 174) +* 09/01/2017 ([Microsoft/LightGBM@9b2558d](https://github.com/microsoft/LightGBM/pull/177)): Feature: devtools R Installation support (Pull Request 177) +* 09/01/2017 ([Microsoft/LightGBM@6219df7](https://github.com/microsoft/LightGBM/pull/175)): Feature: L1 Loss Objective support (Pull Request 175) +* 08/01/2017 ([Microsoft/LightGBM@551d59c](https://github.com/microsoft/LightGBM/pull/168)): Release: R support (Pull Request 168) +* 05/01/2017 ([Microsoft/LightGBM@96d08f4](https://github.com/microsoft/LightGBM/pull/153)): Feature: PMML support (Pull Request 153) +* 01/01/2017 ([Microsoft/LightGBM@a034cee](https://github.com/microsoft/LightGBM/pull/151)): Feature: Pickle support for Python-package (Pull Request 151) +* 26/12/2016 ([Microsoft/LightGBM@96cba41](https://github.com/microsoft/LightGBM/pull/139)): Parameter: DART xgboost support (Pull Request 139) +* 19/12/2016 ([Microsoft/LightGBM@99b483d](https://github.com/microsoft/LightGBM/pull/133)): Parameter: Learning Rate in DART support (Pull Request 133) +* 01/12/2016 ([Microsoft/LightGBM@16d1853](https://github.com/microsoft/LightGBM/pull/94)): Release: Python support (Pull Request 94) +* 11/11/2016 ([Microsoft/LightGBM@98be7e3](https://github.com/microsoft/LightGBM/pull/67)): Feature: DART booster support (Pull Request 67) +* 08/11/2016 ([Microsoft/LightGBM@785398a](https://github.com/microsoft/LightGBM/pull/69)): Parameter: L1 Regularization, L2 Regularization, Minimum Gain to Split support (Pull Request 69) +* 05/11/2016 ([Microsoft/LightGBM@1466f90](https://github.com/microsoft/LightGBM/pull/108)): Release: Categorical Feature support (Pull Request 108) +* 01/11/2016 ([Microsoft/LightGBM@aa796a8](https://github.com/microsoft/LightGBM/pull/53)): Feature: Multiclass classification support (Pull Request 53) +* 28/10/2016 ([Microsoft/LightGBM@c45d1d9](https://github.com/microsoft/LightGBM/pull/42)): Feature: Feature Importance support (Pull Request 42) +* 25/10/2016 ([Microsoft/LightGBM@a6a75fe](https://github.com/microsoft/LightGBM/pull/35)): Parameter: Maximum Depth support (Pull Request 35) +* 24/10/2016 ([Microsoft/LightGBM@9fe0dea](https://github.com/microsoft/LightGBM/pull/30)): Parameter: Leaf Index Prediction support (Pull Request 30) +* 21/10/2016 ([Microsoft/LightGBM@7aaba32](https://github.com/microsoft/LightGBM/pull/27)): Parameter: Early Stopping support (Pull Request 27) with original ([Microsoft/LightGBM@7d4b6d4](https://github.com/microsoft/LightGBM/pull/21) on 20/10/2017, Pull Request 21) * 17/10/2016 ([Microsoft/LightGBM@65ddd85](https://github.com/guFalcon/LightGBM/commit/65ddd852d8d160d86080c45512bd435d15837927)): Release: LightGBM compilable (Commit) diff --git a/docs/Parallel-Learning-Guide.rst b/docs/Parallel-Learning-Guide.rst index 5a6b6737456..e575eeab412 100644 --- a/docs/Parallel-Learning-Guide.rst +++ b/docs/Parallel-Learning-Guide.rst @@ -124,4 +124,4 @@ Example .. _here: https://www.youtube.com/watch?v=iqzXhp5TxUY -.. _A simple parallel example: https://github.com/Microsoft/lightgbm/tree/master/examples/parallel_learning +.. _A simple parallel example: https://github.com/microsoft/lightgbm/tree/master/examples/parallel_learning diff --git a/docs/Parameters.rst b/docs/Parameters.rst index 7c89ecb0160..99d5a2bb1c8 100644 --- a/docs/Parameters.rst +++ b/docs/Parameters.rst @@ -366,7 +366,7 @@ Learning Control Parameters - **Note**: the forced split logic will be ignored, if the split makes gain worse - - see `this file `__ as an example + - see `this file `__ as an example - ``refit_decay_rate`` :raw-html:`🔗︎`, default = ``0.9``, type = double, constraints: ``0.0 <= refit_decay_rate <= 1.0`` diff --git a/docs/Python-Intro.rst b/docs/Python-Intro.rst index f9a15e80b28..e0622e45f85 100644 --- a/docs/Python-Intro.rst +++ b/docs/Python-Intro.rst @@ -5,7 +5,7 @@ This document gives a basic walkthrough of LightGBM Python-package. **List of other helpful links** -- `Python Examples `__ +- `Python Examples `__ - `Python API <./Python-API.rst>`__ @@ -226,4 +226,4 @@ If early stopping is enabled during training, you can get predictions from the b ypred = bst.predict(data, num_iteration=bst.best_iteration) -.. _Python-package: https://github.com/Microsoft/LightGBM/tree/master/python-package +.. _Python-package: https://github.com/microsoft/LightGBM/tree/master/python-package diff --git a/docs/Quick-Start.rst b/docs/Quick-Start.rst index 1ed28dca7ca..12303ae0b17 100644 --- a/docs/Quick-Start.rst +++ b/docs/Quick-Start.rst @@ -71,13 +71,13 @@ For example, the following command line will keep ``num_trees=10`` and ignore th Examples -------- -- `Binary Classification `__ +- `Binary Classification `__ -- `Regression `__ +- `Regression `__ -- `Lambdarank `__ +- `Lambdarank `__ -- `Parallel Learning `__ +- `Parallel Learning `__ .. _CSV: https://en.wikipedia.org/wiki/Comma-separated_values diff --git a/docs/README.rst b/docs/README.rst index 7c8871c2e80..172f8af2c81 100644 --- a/docs/README.rst +++ b/docs/README.rst @@ -5,8 +5,8 @@ Documentation for LightGBM is generated using `Sphinx `__, which works on top of `Doxygen `__ output. List of parameters and their descriptions in `Parameters.rst <./Parameters.rst>`__ -is generated automatically from comments in `config file `__ -by `this script `__. +is generated automatically from comments in `config file `__ +by `this script `__. After each commit on ``master``, documentation is updated and published to `Read the Docs `__. diff --git a/examples/README.md b/examples/README.md index d5a76aa1857..621d2a8d085 100644 --- a/examples/README.md +++ b/examples/README.md @@ -3,7 +3,7 @@ Examples You can learn how to use LightGBM by these examples. -Comments in configuration files might be outdated. Actual information about parameters always can be found [here](https://github.com/Microsoft/LightGBM/blob/master/docs/Parameters.rst). +Comments in configuration files might be outdated. Actual information about parameters always can be found [here](https://github.com/microsoft/LightGBM/blob/master/docs/Parameters.rst). Machine Learning Challenge Winning Solutions ============================================ diff --git a/examples/parallel_learning/README.md b/examples/parallel_learning/README.md index de435f39a97..11c1d2607e2 100644 --- a/examples/parallel_learning/README.md +++ b/examples/parallel_learning/README.md @@ -18,4 +18,4 @@ Here is an example for LightGBM to perform parallel learning for 2 machines. This parallel learning example is based on socket. LightGBM also supports parallel learning based on mpi. -For more details about the usage of parallel learning, please refer to [this](https://github.com/Microsoft/LightGBM/blob/master/docs/Parallel-Learning-Guide.rst). +For more details about the usage of parallel learning, please refer to [this](https://github.com/microsoft/LightGBM/blob/master/docs/Parallel-Learning-Guide.rst). diff --git a/examples/python-guide/README.md b/examples/python-guide/README.md index 87fe10413b1..aba3c9f51d7 100644 --- a/examples/python-guide/README.md +++ b/examples/python-guide/README.md @@ -3,7 +3,7 @@ Python-package Examples Here is an example for LightGBM to use Python-package. -You should install LightGBM [Python-package](https://github.com/Microsoft/LightGBM/tree/master/python-package) first. +You should install LightGBM [Python-package](https://github.com/microsoft/LightGBM/tree/master/python-package) first. You also need scikit-learn, pandas, matplotlib (only for plot example), and scipy (only for logistic regression example) to run the examples, but they are not required for the package itself. You can install them with pip: @@ -19,19 +19,19 @@ python simple_example.py Examples include: -- [simple_example.py](https://github.com/Microsoft/LightGBM/blob/master/examples/python-guide/simple_example.py) +- [simple_example.py](https://github.com/microsoft/LightGBM/blob/master/examples/python-guide/simple_example.py) - Construct Dataset - Basic train and predict - Eval during training - Early stopping - Save model to file -- [sklearn_example.py](https://github.com/Microsoft/LightGBM/blob/master/examples/python-guide/sklearn_example.py) +- [sklearn_example.py](https://github.com/microsoft/LightGBM/blob/master/examples/python-guide/sklearn_example.py) - Create data for learning with sklearn interface - Basic train and predict with sklearn interface - Feature importances with sklearn interface - Self-defined eval metric with sklearn interface - Find best parameters for the model with sklearn's GridSearchCV -- [advanced_example.py](https://github.com/Microsoft/LightGBM/blob/master/examples/python-guide/advanced_example.py) +- [advanced_example.py](https://github.com/microsoft/LightGBM/blob/master/examples/python-guide/advanced_example.py) - Construct Dataset - Set feature names - Directly use categorical features without one-hot encoding @@ -47,12 +47,12 @@ Examples include: - Self-defined objective function - Self-defined eval metric - Callback function -- [logistic_regression.py](https://github.com/Microsoft/LightGBM/blob/master/examples/python-guide/logistic_regression.py) +- [logistic_regression.py](https://github.com/microsoft/LightGBM/blob/master/examples/python-guide/logistic_regression.py) - Use objective `xentropy` or `binary` - Use `xentropy` with binary labels or probability labels - Use `binary` only with binary labels - Compare speed of `xentropy` versus `binary` -- [plot_example.py](https://github.com/Microsoft/LightGBM/blob/master/examples/python-guide/plot_example.py) +- [plot_example.py](https://github.com/microsoft/LightGBM/blob/master/examples/python-guide/plot_example.py) - Construct Dataset - Train and record eval results for further plotting - Plot metrics recorded during training diff --git a/include/LightGBM/config.h b/include/LightGBM/config.h index 6f270630656..2a6896f82dc 100644 --- a/include/LightGBM/config.h +++ b/include/LightGBM/config.h @@ -372,7 +372,7 @@ struct Config { // desc = ``.json`` file can be arbitrarily nested, and each split contains ``feature``, ``threshold`` fields, as well as ``left`` and ``right`` fields representing subsplits // desc = categorical splits are forced in a one-hot fashion, with ``left`` representing the split containing the feature value and ``right`` representing other values // desc = **Note**: the forced split logic will be ignored, if the split makes gain worse - // desc = see `this file `__ as an example + // desc = see `this file `__ as an example std::string forcedsplits_filename = ""; // check = >=0.0 diff --git a/python-package/README.rst b/python-package/README.rst index 6d72c84bf78..7563a255dcd 100644 --- a/python-package/README.rst +++ b/python-package/README.rst @@ -24,7 +24,7 @@ For **macOS** users: - Starting from version 2.2.1, the library file in distribution wheels is built by the **Apple Clang** (Xcode_8.3.3) compiler. This means that you don't need to install the **gcc** compiler anymore. Instead of that you need to install the **OpenMP** library, which is required for running LightGBM on the system with the **Apple Clang** compiler. You can install the **OpenMP** library by the following command: ``brew install libomp``. -- For version smaller than 2.2.1 and not smaller than 2.1.2, **gcc-8** with **OpenMP** support must be installed first. Refer to `Installation Guide `__ for installation of **gcc-8** with **OpenMP** support. +- For version smaller than 2.2.1 and not smaller than 2.1.2, **gcc-8** with **OpenMP** support must be installed first. Refer to `Installation Guide `__ for installation of **gcc-8** with **OpenMP** support. - For version smaller than 2.1.2, **gcc-7** with **OpenMP** is required. @@ -45,7 +45,7 @@ For **Linux** and **macOS** users, installation from sources requires installed For **macOS** users, you can perform installation either with **Apple Clang** or **gcc**. -- In case you prefer **Apple Clang**, you should install **OpenMP** (details for installation can be found in `Installation Guide `__) first and **CMake** version 3.12 or higher is required. +- In case you prefer **Apple Clang**, you should install **OpenMP** (details for installation can be found in `Installation Guide `__) first and **CMake** version 3.12 or higher is required. In some cases **OpenMP** cannot be found which causes installation failures. So, if you encounter errors during the installation process, try to pass paths to **CMake** via ``pip`` options, like @@ -53,7 +53,7 @@ For **macOS** users, you can perform installation either with **Apple Clang** or pip install lightgbm --install-option="--openmp-include-dir=/usr/local/opt/libomp/include/" --install-option="--openmp-library=/usr/local/opt/libomp/lib/libomp.dylib" -- In case you prefer **gcc**, you need to install it (details for installation can be found in `Installation Guide `__) and specify compilers by running ``export CXX=g++-7 CC=gcc-7`` (replace "7" with version of **gcc** installed on your machine) first. +- In case you prefer **gcc**, you need to install it (details for installation can be found in `Installation Guide `__) and specify compilers by running ``export CXX=g++-7 CC=gcc-7`` (replace "7" with version of **gcc** installed on your machine) first. For **Windows** users, **Visual Studio** (or `VS Build Tools `_) is needed. If you get any errors during installation, you may need to install `CMake`_ (version 3.8 or higher). @@ -79,7 +79,7 @@ All remarks from `Build from Sources section <#build-from-sources>`__ are actual For **Windows** users, compilation with **MinGW-w64** is not supported and `CMake`_ (version 3.8 or higher) is strongly required. -**MPI** libraries are needed: details for installation can be found in `Installation Guide `__. +**MPI** libraries are needed: details for installation can be found in `Installation Guide `__. Build GPU Version ~~~~~~~~~~~~~~~~~ @@ -92,7 +92,7 @@ All remarks from `Build from Sources section <#build-from-sources>`__ are actual For **Windows** users, `CMake`_ (version 3.8 or higher) is strongly required. -**Boost** and **OpenCL** are needed: details for installation can be found in `Installation Guide `__. Almost always you also need to pass ``OpenCL_INCLUDE_DIR``, ``OpenCL_LIBRARY`` options for **Linux** and ``BOOST_ROOT``, ``BOOST_LIBRARYDIR`` options for **Windows** to **CMake** via ``pip`` options, like +**Boost** and **OpenCL** are needed: details for installation can be found in `Installation Guide `__. Almost always you also need to pass ``OpenCL_INCLUDE_DIR``, ``OpenCL_LIBRARY`` options for **Linux** and ``BOOST_ROOT``, ``BOOST_LIBRARYDIR`` options for **Windows** to **CMake** via ``pip`` options, like .. code:: sh @@ -132,7 +132,7 @@ Build with MinGW-w64 on Windows `CMake`_ and `MinGW-w64 `_ should be installed first. -It is recommended to use **Visual Studio** for its better multithreading efficiency in **Windows** for many-core systems (see `FAQ `__ Question 4 and Question 8). +It is recommended to use **Visual Studio** for its better multithreading efficiency in **Windows** for many-core systems (see `FAQ `__ Question 4 and Question 8). Install from GitHub ''''''''''''''''''' @@ -145,7 +145,7 @@ For **Windows** users, if you get any errors during installation and there is th .. code:: sh - git clone --recursive https://github.com/Microsoft/LightGBM.git + git clone --recursive https://github.com/microsoft/LightGBM.git cd LightGBM/python-package # export CXX=g++-7 CC=gcc-7 # macOS users, if you decided to compile with gcc, don't forget to specify compilers (replace "7" with version of gcc installed on your machine) python setup.py install @@ -162,19 +162,19 @@ Run ``python setup.py install --gpu`` to enable GPU support. All remarks from `B Run ``python setup.py install --hdfs`` to enable HDFS support. All remarks from `Build HDFS Version section <#build-hdfs-version>`__ are actual in this case. -If you get any errors during installation or due to any other reasons, you may want to build dynamic library from sources by any method you prefer (see `Installation Guide `__) and then just run ``python setup.py install --precompile``. +If you get any errors during installation or due to any other reasons, you may want to build dynamic library from sources by any method you prefer (see `Installation Guide `__) and then just run ``python setup.py install --precompile``. Troubleshooting --------------- In case you are facing any errors during the installation process, you can examine ``$HOME/LightGBM_compilation.log`` file, in which all operations are logged, to get more details about occurred problem. Also, please attach this file to the issue on GitHub to help faster indicate the cause of the error. -Refer to `FAQ `_. +Refer to `FAQ `_. Examples -------- -Refer to the walk through examples in `Python guide folder `_. +Refer to the walk through examples in `Python guide folder `_. Development Guide ----------------- @@ -194,7 +194,7 @@ E501 (line too long) and W503 (line break occurred before a binary operator) can Documentation strings (docstrings) are written in the NumPy style. .. |License| image:: https://img.shields.io/badge/license-MIT-blue.svg - :target: https://github.com/Microsoft/LightGBM/blob/master/LICENSE + :target: https://github.com/microsoft/LightGBM/blob/master/LICENSE .. |Python Versions| image:: https://img.shields.io/pypi/pyversions/lightgbm.svg :target: https://pypi.org/project/lightgbm .. |PyPI Version| image:: https://img.shields.io/pypi/v/lightgbm.svg diff --git a/python-package/lightgbm/__init__.py b/python-package/lightgbm/__init__.py index 75a4db5c848..7b55fb10865 100644 --- a/python-package/lightgbm/__init__.py +++ b/python-package/lightgbm/__init__.py @@ -1,7 +1,7 @@ # coding: utf-8 """LightGBM, Light Gradient Boosting Machine. -Contributors: https://github.com/Microsoft/LightGBM/graphs/contributors. +Contributors: https://github.com/microsoft/LightGBM/graphs/contributors. """ from __future__ import absolute_import diff --git a/python-package/setup.py b/python-package/setup.py index e89ede2ff60..e0e80d97d77 100644 --- a/python-package/setup.py +++ b/python-package/setup.py @@ -319,7 +319,7 @@ def run(self): packages=find_packages(), include_package_data=True, license='The MIT License (Microsoft)', - url='https://github.com/Microsoft/LightGBM', + url='https://github.com/microsoft/LightGBM', classifiers=['Development Status :: 5 - Production/Stable', 'Intended Audience :: Science/Research', 'License :: OSI Approved :: MIT License', diff --git a/tests/python_package_test/test_sklearn.py b/tests/python_package_test/test_sklearn.py index b47e18db544..31c06f72ca8 100644 --- a/tests/python_package_test/test_sklearn.py +++ b/tests/python_package_test/test_sklearn.py @@ -192,7 +192,7 @@ def test_sklearn_integration(self): for name, estimator in ((lgb.sklearn.LGBMClassifier.__name__, lgb.sklearn.LGBMClassifier), (lgb.sklearn.LGBMRegressor.__name__, lgb.sklearn.LGBMRegressor)): check_parameters_default_constructible(name, estimator) - # we cannot leave default params (see https://github.com/Microsoft/LightGBM/issues/833) + # we cannot leave default params (see https://github.com/microsoft/LightGBM/issues/833) estimator = estimator(min_child_samples=1, min_data_in_bin=1) for check in _yield_all_checks(name, estimator): check_name = check.func.__name__ if hasattr(check, 'func') else check.__name__ diff --git a/windows/LightGBM.sln b/windows/LightGBM.sln index d10aaa5824f..189d7d4e735 100644 --- a/windows/LightGBM.sln +++ b/windows/LightGBM.sln @@ -1,4 +1,4 @@ - + Microsoft Visual Studio Solution File, Format Version 12.00 # Visual Studio 14 VisualStudioVersion = 14.0.25420.1 diff --git a/windows/LightGBM.vcxproj b/windows/LightGBM.vcxproj index b2cfd42d2a4..7a0ddde938f 100644 --- a/windows/LightGBM.vcxproj +++ b/windows/LightGBM.vcxproj @@ -1,4 +1,4 @@ - + @@ -283,4 +283,4 @@ - \ No newline at end of file + diff --git a/windows/LightGBM.vcxproj.filters b/windows/LightGBM.vcxproj.filters index 0993b34b0be..3b770e40dab 100644 --- a/windows/LightGBM.vcxproj.filters +++ b/windows/LightGBM.vcxproj.filters @@ -1,4 +1,4 @@ - + @@ -303,4 +303,4 @@ src\io - \ No newline at end of file +