GitLab

* update sklearn fit parameter description

* update mtric parameter description

* fixed PyPI badge

* Update Parameters.rst

* Update Parameters.rst

* Update Parameters.rst

fix #1288

* fix the bug

* fix R

* added comment to not forget

* updated LGBMClassifier according to new aliases

[python] added option to install python-package with mpi version and possibility to pass CMake options (#1034)

* fixed hierarchy of installation guide sections; made installation with proto support more verbose

* added option to install with protobuf support to python package

* fixed pylint

* added option to install MPI version to python package

* added tests for python-package installation with options --proto and --mpi

* hotfix

* removed unnecessary note from docs

* removed unnecessary line from travis script

* reverted proto

* Revert "reverted proto"

This reverts commit 5203448bb90a13844cf330527ca971eabb45a4a8.

* reverted protobuf from python-package

* added options for cmake in python-package

* fixed typos

* fixed options readability

* reworked installation logging

* fixed docs according to review comments

* fixed pylint

* fixed space in log path

* avoid to set all weight to 1.

* fix valid_class_weight

* added class_weight parameter in sklearn wrapper

* added note about alternative parameters in case of binary classification task

* fix early stopping edge case

* fix message.

* fix tests

* fix GPU tests.

* add try/except to __del__

* specify AttributeError

* Add n_estimators as num_iteration alias

Scikit-Learn's ensemble methods use the term `n_estimators` for the number of
iterations of training models. To make it more accessible for newcomers who are
familiar with Scikit-Learn, it would help if the Parameters page mentioned
`n_estimators` and what parameter that maps to within LightGBM's API.

Addresses discussion brought up in #954

* Add n_estimators as num_iterations alias

Adds n_estimators as an alias for num_iterations in the CLI as well as Python
libs. Additionally bumps the default for n_estimators in the Sklearn API to 100
estimators.

* updated travis

* renamed OSX->macOS; updated gcc installation on macOS

* updated travis macos installation

 Please enter the commit message for your changes. Lines starting

* updated installation guide for macos

* fixed spelling

* renamed appveyor file

* updated Travis

* remove protobuf

* add version number

* remove pmml script

* use float for split gain

* fix warnings

* refine the read model logic of gbdt

* fix compile error

* improve decode speed

* fix some bugs

* fix double accuracy problem

* fix bug

* multi-thread save model

* speed up save model to string

* parallel save/load model

* fix some warnings.

* fix warnings.

* fix a bug

* remove debug output

* fix doc

* fix max_bin warning in tests.

* fix max_bin warning

* fix pylint

* clean code for stringToArray

* clean code for TToString

* remove max_bin

* replace "class" with typename

* use int64 for string

* [R] Fatal when CSC exceed int32.max

[python] [docs] fixed objective in sklearn wrapper; added missed objectives & metrics to docs (#1059)

* added missed aliases for task parameter

* fixed indents

* added missed aliases and options for tree_learner parameter

* added missed objectives to docs

* fixed typo in Poisson parameter and its description

* fixed model_format parameter description

* added missed metrics to docs

* fixed sklearn objective

* fixed set_params

* fixed docs

* added missed options to objectives

* added note about ignore_column (#1061)

* made max_bin parameter deprecated

* fixed accidental docstrings in Sphinx

* concrete version when deprecated stuff will be removed

* added warnings in case of duplicated params to Dataset

* fixed indents in docs

* add init_score & test cpp and python result consistency

* try fix common.h

* Fix tests (#3)

* update atof

* fix bug

* fix tests.

* fix bug

* fix dtypes

* fix categorical feature override

* fix protobuf on vs build (#1004)

* [optional] support protobuf

* fix windows/LightGBM.vcxproj

* add doc

* fix doc

* fix vs support (#2)

* fix vs support

* fix cmake

* fix #1012

* [python] add network config api  (#1019)

* add network

* update doc

* add float tolerance in bin finder.

* fix a bug

* update tests

* add double torelance on tree model

* fix tests

* simplify the double comparison

* fix lightsvm zero base

* move double tolerance to the bin finder.

* fix pylint

* clean test.sh

* add sklearn test

* remove underline

* clean codes

* set random_state=None

* add last line

* fix doc

* rename file

* try fix test

* fixed parameters consistent

* added aliases to docs

* added missed parameter top_k

* fixed ignored subsample_for_bin parameter

* added missed aliases to Quick Start Guide

* fixed docs building at Python 2.x

* updated docs building guide

* get back Python 3 at Travis

* test commit for OSX

* be more precise with python version inpylint task

* turned warnings into errors

* removed linkchecker validation from osx

* removed warning about not included into any toctree

* docs config cleanup

* refined deprecation warnings mechanism

* refine docs mock mechanism

* be more precise with python version in check-docs task

* redused the number of code lines

* refined venv deployment

* rollback python version in check-docs task

* revert 'refine docs mock mechanism'. autodoc_mock_imports seems to be not working

* added targets for big images

* rollback to default python version in check-docs task

* break long lines for mobile view

* replaced pip with conda where it's possible

* add network

* update doc

* added validation of python-package folder

* fixed duplicate explicit targets names

* many fixes for categorical feature

* add l2 to categorcial split.

* remove useless file

* update version

* add cat_l2

* update appveyor verison

* remove file

* fix tests.

* change default cat_l2 value

* fix a bug in bin finder

* change default cat_smooth_ratio