[docs] updated Microsoft GitHub URL (#2152)

* fix travis badge

* updated GitHub Microsoft URL

.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)) {

.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

.nuget/create_nuget.py

@@ -34,8 +34,8 @@
         <version>%s</version>
         <authors>Guolin Ke</authors>
         <owners>Guolin Ke</owners>
-        <licenseUrl>https://github.com/Microsoft/LightGBM/blob/master/LICENSE</licenseUrl>
-        <projectUrl>https://github.com/Microsoft/LightGBM</projectUrl>
+        <licenseUrl>https://github.com/microsoft/LightGBM/blob/master/LICENSE</licenseUrl>
+        <projectUrl>https://github.com/microsoft/LightGBM</projectUrl>
         <requireLicenseAcceptance>false</requireLicenseAcceptance>
         <description>A fast, distributed, high performance gradient boosting framework</description>
         <copyright>Copyright %d @ Microsoft</copyright>

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**.
 
@@ -89,29 +89,29 @@ 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:
 
 ```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:
 
 ```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
 --------

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.

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,

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.

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

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 <https://github.com/Microsoft/LightGBM/blob/master/include/LightGBM/c_api.h>`__ file, from which the documentation is generated.
+Refer to `C API <./C-API.rst>`__ or the comments in `c\_api.h <https://github.com/microsoft/LightGBM/blob/master/include/LightGBM/c_api.h>`__ file, from which the documentation is generated.
 
 High Level Language Package
 ---------------------------
 
-See the implementations at `Python-package <https://github.com/Microsoft/LightGBM/tree/master/python-package>`__ and `R-package <https://github.com/Microsoft/LightGBM/tree/master/R-package>`__.
+See the implementations at `Python-package <https://github.com/microsoft/LightGBM/tree/master/python-package>`__ and `R-package <https://github.com/microsoft/LightGBM/tree/master/R-package>`__.
 
 Questions
 ---------
 
 Refer to `FAQ <./FAQ.rst>`__.
 
-Also feel free to open `issues <https://github.com/Microsoft/LightGBM/issues>`__ if you met problems.
+Also feel free to open `issues <https://github.com/microsoft/LightGBM/issues>`__ if you met problems.