GitLab

* decode error description

* added break line char in log massages

* first draft

* refine a branching

* added code to expose c_api_pred_contrib in the R package

* removed Rprintf

* reverted to previous version of install.libs.R

* Read and write datsets from hdfs.
* Only enabled when cmake is run with -DUSE_HDFS:BOOL=TRUE
* Introduces VirtualFile(Reader|Writer) to asbtract VFS differences

* fix a bug in `ArgMaxAtK`

* 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

* update network.h

Improve training speed in parallel learning where workers is not powers of 2

* update linders_socket.cpp

Improve training speed in parallel learning where workers is not powers of 2

* update linder_topo.cpp

Improve training speed in parallel learning where workers is not powers of 2

* update network.cpp

Improve training speed in parallel learning where workers is not powers of 2

* update linder_topo.cpp

fix a bug

* refine allgather.

* fix a bug.

* 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.

* fix feature fraction

* fix bugs.

* 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

add 'null' to missing value

[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)