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* 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.

* 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

* 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

* fixed Python-API references

* moved Features section to ReadTheDocs

* fixed index of ReadTheDocs

* moved Experiments section to ReadTheDocs

* fixed capital letter

* fixed citing

* moved Parallel Learning section to ReadTheDocs

* fixed markdown

* fixed Python-API

* fixed link to Quick-Start

* fixed gpu docker README

* moved Installation Guide from wiki to ReadTheDocs

* removed references to wiki

* fixed capital letters in headings

* hotfixes

* fixed non-Unicode symbols and reference to Python API

* fixed citing references

* fixed links in .md files

* fixed links in .rst files

* store images locally in the repo

* fixed missed word

* fixed indent in Experiments.rst

* fixed 'Duplicate implicit target name' message which is successfully
resolved by adding anchors

* less verbose

* prevented maito: ref creation

* fixed indents

* fixed 404

* fixed 403

* fixed 301

* fixed fake anchors

* fixed file extentions

* fixed Sphinx warnings

* added StrikerRUS profile link to FAQ

* added henry0312 profile link to FAQ

* added test for sklearn handle categorical features

* use raw X, y in sklearn wrapper in case of pandas.DataFrame

* fixed probs

* Fix feature attributions for regression models and add Python bindings

* Address pylint issue

* Lazy fix missing tree depth info

* travis cleanup

* removed precompiled files in windows folder from sdist command

* removed rubbish from install folder

* added compute folder

* disabled logs from compilers; fixed #874

* fixed safe clear_fplder

* added windows folder to manifest.in

* added windows folder to build

* added library path

* added compilation with MSBuild from .sln-file

* fixed unknown PlatformToolset returns exitcode 0

* hotfix

* updated Readme

* removed return

* added installation with mingw test to appveyor

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

* fixed built-in name 'file'

* simplified appveyor

* removed excess data_files

* fixed unreadable paths

* separated exceptions for cmake and mingw

* refactored silent_call

* don't create artifacts with VS 2015 and mingw

* be more precise with python versioning in Travis

* removed unnecessary if statement

* added classifiers for PyPI and python versions badge

* changed python version in travis

* added support of scikit-learn 0.18.x

* added more python versions to Travis

* added more python versions to Appveyor

* reduced number of tests in Travis

* Travis trick is not needed anymore

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

* fixed description of Dataset

* fixed description of Booster

* fixed description of train

* fixed description of cv

* fixed description of callbacks

* fixed description of plotting

* hotfixes

This commit will regain backward compatibility that has been broken
after 015c8fff.

* improved sklearn interface; added sklearns' tests

* moved best_score into the if statement

* improved docstrings; simplified LGBMCheckConsistentLength

* fixed typo

* pylint

* updated example

* fixed Ranker interface

* added missed boosting_type

* fixed more comfortable autocomplete without unused objects

* removed check for None of eval_at

* fixed according to review

* fixed typo

* added description of fit return type

* dictionary->dict for short

* markdown cleanup

* expose feature importance to c_api

* support type=gain

* remove dump model from examples and tests temporarily because it's unstable

* use double instead of float

* updated scikit-learn interface

* fixed better description

* updated set_params()

* removed backward compatibility

* removed excess lines

* replaced pop with setdefault

* added deprecated warnings

* added tests

* try to fix python memory leak

* fix parameter error.

* free old handle in _load_model_from_string .

* fix best_score & best_iteration

* refine logics.

* fix tests.

* python-package: fix version

* remove version variable

* check params

* add test case

* fix pylint

* Fix Invalid decision type error while plotting tree in Python

* Fix Invalid decision type error while plotting tree in Python (modified = to ==)

* params back up

* refine logic

* refine python codes

* fix appveryor test

* add note to feature_importances

* added get_ref_chain function to Dataset object, used it in train() to compare if training and validation have common reference ancestors

* moved check of common ancestor reference from train() in engine.py to set_reference() in Dataset

* moved check of common ancestor reference from train() in engine.py to set_reference() in Dataset

* removed check for handle = None