GitLab

refine Objective Parameters section

* refine IO Parameters section

* added missed alias of init_score

* fixed grammar

* fixed gpu test according new config file

* refine Learning Control Parameters section

* added missed check for length consistency of valid and valid init scores

* added missed aliases for core params

* 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

* 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

* [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.

* decode error description

* added break line char in log massages

* first draft

* refine a branching

* 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)

* add quantile metric.

* first draft.

* add "sqrt" transform in regression objective function.

* fix a bug.

* update parameter doc

* fix doc

* 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

* [optional] support protobuf

* fix windows/LightGBM.vcxproj

* add doc

* fix doc

* fix vs support (#2)

* fix vs support

* fix cmake

This reverts commit 53b99854.

commit c9e123f24fcbb159c04e6694c7f830530bb2f27e
Author: Guolin Ke <i@yumumu.me>
Date:   Wed Oct 18 10:00:19 2017 +0800

    change default max_cat_to_onehot

commit 805a5c3125b9979d634922e1708877fa0fec80c6
Author: Guolin Ke <i@yumumu.me>
Date:   Tue Oct 17 22:57:18 2017 +0800

    use one hot coding for the small cats

* 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

* add network apis.

* support parallel loading dataset in c api.

* fix bug

* fix bug

* add get params

clean codes

* check duplicate params

* Revert "add get params"

This reverts commit ec1d8dd17aa2c83dd0d5f7716c59b6a6fb94102c.

* set priority by length & check duplicate

* rename function

* refine categorical split

* add test

* output warning when only set `max_depth`

* Remove check of max_depth

max_depth can take both positive and negative value

* Explain individual predictions using SHAP value feature attributions

* Address code review

* finish the data loading part

* allow prediction.

* fix bug for decision type.

* finish split finding part

* fix bugs.

* bug fixed. add a test .

* fix pep8 .

* update documents.

* fix test bugs.

* fix a format

* fix import error in python test.

* disable missing handle in categorial features.

* fix a bug.

* add more tests.

* fix pep8

* fix bugs.

* remove the missing handle code for categorical feature.

* Created objectives and metrics xentropy and xentropy1

* Some coment and code cleanup.

* Added Kullback-Leibler version of metric. Changed some warning messages.

* Fixed sign error in KL-divergence calc.

* Removed __PRETTY_FUNCTION__.

* Fixed better name for alternative xentropy parameterization.
Documented details on the objectives / metrics in code comments.

* Common code for label interval checks. Cleanups.

* Use common utility for various weight property checks.

* Added code for customizable initial average to boost from.

* Fixed spelling error in aliases.