GitLab

* ignore vim temporary files

* add importance_type arg to sklearn API

* update documentation info

* remote a trailing space

* remove trailing space (again :))

* add instructions on importance choices to sklearn API

* drop mention of constructor in the feature type setting

* adding a test for different feture types

* remove trailing spaces, make shorter assert in feature importance type handling test

* fixing style issue introduced with the new test

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.

* 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

* added comment to not forget

* updated LGBMClassifier according to new aliases

* 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

* 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

[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

* 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

* 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

* 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

* refine python codes

* fix appveryor test

* add note to feature_importances

eval_at has been broken after e465f92a.
This commit will fix eval_at.

This commit will regain backward compatibility that has been broken
after e465f92a.

* check parameters

* refine sklearn verbose logic

* fix segfault

* Warning -> Fatal

* fix segfault

* support kwargs for sklearn

* add link to Parameters

This commit follows Microsoft/LightGBM@3abff37

* python-package: fix creating eval_set in LGBMClassifier

* replace elements in eval_set directly