GitLab

* it is confusing to name validation data `test_data` especially as terms like train, validation, test splits are common in ML. Change variable name in python quick start.

* Update VERSION.txt

* Update .appveyor.yml

* Update DESCRIPTION

* Update DESCRIPTION

* Update DESCRIPTION

* Hand edit broken commit

* Hand edit broken commit

* Hand edit broken commit

* Hand edit broken commit

* convert datatable to numpy directly

* fix according to comments

* updated more docstrings

* simplified isinstance check

* Update compat.py

[docs] Fixed OpenCL Debian package name typo

* refined command status check

* refined Appveyor

* redirect all warnings to stdout

* added OpenMP options for python-package installation

* fixed grammar typo

* always save the score of the first round in early stopping

fix #1971

* avoid using std::log on non-positive numbers

* remove unnecessary changes

* add tests

* Update test_sklearn.py

* enhanced tests

* added test for huge string model

* fixed tree sizes field

* simplified model structure

* fixed test and added try/except

[tests][python] added tests for metrics' behavior and fixed case for multiclass task with custom objective (#1954)

* added metrics test for standard interface

* simplified code

* less trees

* less trees

* use dummy custom objective and metric

* added tests for multiclass metrics aliases

* fixed bug in case of custom obj and num_class > 1

* added metric test for sklearn wrapper

* Fix build on macOS Mojave

Fixed #1898

- https://iscinumpy.gitlab.io/post/omp-on-high-sierra/
- https://cliutils.gitlab.io/modern-cmake/chapters/packages/OpenMP.html
- https://github.com/Homebrew/homebrew-core/pull/20589

* update setup.py

* update docs

* fix setup.py

* update docs

* update docs

* update setup.py

* update docs

* add warnings for override parameters of Dataset

* fix pep8

* add feature_penalty

* refactor

* add R's code

* Update basic.py

* Update basic.py

* fix parameter bug

* Update lgb.Dataset.R

* fix a bug

* fixed minor typos in documentation

* fixed typo in gpu_tree_learner.cpp

* Update .gitignore

* Added links to the libraries used.

* Fixing the header

* Fixes

* ot -> to

* Correcting lgb.prepare output comment

* updated Roxygen files

* Fix multiclass custom objective demo

* Use option not to boost from average instead of setting init score explicitly

* Reference #1846 when turning off boost_from_average

* Add trailing whitespace

* removed comparison warning

* fixed spacing

* removed brew hotfix and deprecated sudo option on Travis

* removed brew hotfix on Azure

File: [LightGBM//src/io/dataset.cpp]
Function: [138:FastFeatureBundling(...)]

Reserving vectors where we already know the size to save on reallocation costs.

Also removed a variable that was unnecessary.

When loading a binary file, take feature penalty and monotone constraints from config if given there. (#1881)

* When loading a binary file, take feature penalty from config if given there.

* When loading a binary file, take feature penalty from config if given there.

* Fix crash when num_features != num_total_features and feature_contri is given.

* Apply the same logic to monotone_types_.

* Fix indentation

* fixed xcode version

* fixed brew on Travis

* fixed brew on Azure Pipelines

add boost header files compute/ into build_r.R to enable GPU compilation