GitLab

* fixed grammar

* fixed params description in graph plotting functions

* clarified types of attributes in their descriptions

* increased readability of graphs by adding spaces

* added precision parameter to plot tree functions

* added missed description of plot_example in python_guide folder and fixed consistency for packages naming

* more reliable OS detection

* fixed grammar

* made pylint happy

The document of `early_stopping_rounds` says it will check all of
eval_set. But, this is not true. It doesn't check the dataset
specified as the training data.

This change appends an extra phrase "except the training data" to all
of the sentences "If there's more than one, will check all of them" in
documents.

* added checks for categorical features > max_int32

* added tests

* fixed pylint

* removed warnings about overridden categorical features

* Revert "removed warnings about overridden categorical features"

This reverts commit 289a426c700ce8934a526cc456a1b1cd5c621db9.

* a little bit more efficient checks

* added notes about max values in categorical features

* Revert "a little bit more efficient checks"

This reverts commit bed88830243da21a2db454873c0e308126e05732.

* Revert "fixed pylint"

This reverts commit a229e1563b0abc1b13de6358577abf90bd529015.

* Revert "added tests"

This reverts commit 299e001b7550111555b80730d673d4f225cf5f74.

* Revert "added checks for categorical features > max_int32"

This reverts commit 2cc7afacde7c6366644f6988ccedc344752b68c7.

* Clarify docs for feval

* docs- adds that feval can be a string

* docs- deletes extraneous space

* decode error description

* added break line char in log massages

* fixed docs

* reworker predict method of sklearn wrapper

* fixed encapsulation

* added test

* fixed consistency between docstring and params docs

* fixed verbose

* replaced predict_proba with predict in test

* fixed verbose again

* fixed fraction params descriptions

* added description of skip_drop and drop_rate constraints

* fixed subsample_freq consistency with C++ default value

* fixed nice look of params list

* made force splits json file example clickable

* fixed nice look of metrics list and added comma

* reduced warning in test about same param specified twice

* replaced pred_parameter with **kwargs in predict method

* added test for **kwargs in predict method

* fixed warnings

* fixed pylint

* updated pep8 to pycodestyle

* fixed E722 do not use bare 'except'

* fixed W605 invalid escape sequence '\*'

* fixed W504 line break after binary operator

* ignore W605 invalid escape sequence '\*' in nuget builder

* made pycodestyle happy

* add info on adaptive learning rate in the sklearn API

* adjust learning rate documentation following the PR discussion

* fix early stopping documentation

* improve wording

* fixing trailing spaces

* update sklearn fit parameter description

* update mtric parameter description

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.

* 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