GitLab

* updated docs of num_iterations parameter

* updated num_iterations param description for R

* fix custom metric for multiclass

* fix alias

* fix bug

* fix indent

* added new aliases for params

* run helper/parameter_generator.py

* removed useless test

* fixed typo in parameter list Parameters.rst

fixed typo from contributs to contributes

* Update config.h

* added permalink to each parameter

* run parameter_generator.py

* concretized links

* hotfix

* run parameter_generator.py

* added space between param name and permalink

* added info about initscore_filename in Continued Training section and edited links

* replaced aliases for weight and group with original names

* disable emoji

* add per-feature-penalites

* fix comment

* removed excess whitespaces

* don't use built-in name for variable

* simplified line parsing

* chanched link to related

* run parameter_generator.py

* removed old targets

* use tuples instead of list where possible

* hotfix for descriptions were erased and only last one was kept

* run parameter_generator.py

* separated checks from aliases section

* generate parameters description from config file

* made pylint happy

* added checks description

* fixed links handling in desc and descl2 fields

* refine Core Parameters section

* removed excess quotes from default values

* fixed parameter type retrieve

* added note about auto-generated parameters

* A nitpicky grammer edit with minor clarifications added.

* fix link

* strike s

* try a different optimal-split link, clarify experimental details

* smoothing the FAQ

* edit Features.rst

* several minor edits throughout docs

* historgram-based

* Note the relationship between `binary` and `xentropy` in the docs and provide an example that compares them

* Pass pylint and fix docs formatting. "pylint: disable = no-name-in-module" because pylint does not believe scipy.special contains expit

* pass pycodestyle

* pass pycodestyle with correct flags; document example in readme

* 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.

* [WIP] refine config

* [wip] ready for the auto code generate

* auto generate config codes

* use with to open file

* fix bug

* fix pylint

* fix bug

* fix pylint

* fix bugs.

* tmp for failed test.

* fix tests.

* added nthreads alias

* added new aliases from new config.h

* fixed duplicated alias

* refactored parameter_generator.py

* added new aliases from config.h and removed remaining old names

* fix bugs & some miss alias

* added aliases

* add more descriptions.

* add comment.

* delegated not showing hidden items to the rtd_theme

* refactored docs

* 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

* update sklearn fit parameter description

* update mtric parameter description

* first draft

* refine a branching

* fixed PyPI badge

* Update Parameters.rst

* Update Parameters.rst

* Update Parameters.rst

* fixed typo

* fixed render of default value of metric param

* fixed typos

* added new aliases for regression_l2 to docs

* fixed new line

* fixed tweedie_variance_power description

* moved gamma and tweedie metrics to other regression metrics

* added new aliases for l2 to docs

* added new alias for l1 to docs

* added new alias for log loss to docs

* added new aliases for multiclass to docs

* added description for default value of metric param

* fixed link to poisson regression and capitalized regressions' names

* removed unused earlier alias type for gamma deviance

* added aliases for multiclass and multiclass_ova

* updated Quick-Start.rst according to Parameters.rst

* added cross-entropy into Features

* added aliases

* unfinished

* some refines.

* fix a bug

* some refines

* remove useless files

* some small fixes

* clean code

* clean code

* fix connect

* fix a broken link

* fix a broken link

* add output_freq to aliases

* reordered params set according to review comment

* add code for refit tree

* add implementation.

* update documents.

* clean code

* fix a type

* 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)