GitLab

* translate model to if-else

* support multiclass and predictleaf

* remove java option for now

* support multi-thread

* add task:convert_model

* refine prediction logic.

* fix test.

* fix out_len in training score of Dart.

* improve predict speed for high dimension data.

* Added possibility to compile without openmp (useful for clang on Mac)

* Added CMake option to create dylib on MacOS

* src & callbacks

* lgb.Booster and utils

* cv

* wip lgb.Dataset

* lgb.Dataset

* lgb.Predictor

* lgb.train

* typos

* add flags to facilitate macosx compilation

* fix basic_string template error with clang

* most unfortunate mode of development

* fixup tests

* last test

* roxygen

* roxygen v5.x.x

Categorical feature support (#108)

1. merge python-package
2. add dump model to json
3. fix bugs
4. clean code with pylint
5. update python examples

* RAII for utils, application and c_api(partical)

* raii for class in include folder

* raii for application and boosting

* raii for dataset and dataset loader

* raii for dense bin and parser

* RAII refactor for almost all classes

* RAII for c_api

* clean code

* refine repeated code

* Decouple the "sigmoid" between objective and boosting.

* change std::vector<bool> back to std::vector<char> due to concurrence problem

* slight reduce some memory cost

add DART: Dropouts meet Multiple Additive Regression Trees (#67)

Packages that parse LightGBM’s logs will require minor changes to
parsing logic to work correctly.

support init_score for multiclass classification (#62)

* a python regression example

* add early-stopping

* fix bugs

* remove not needed files

* update easy-stopping; fix warnings; add alias

* add comments; remove useless line

* change code order

* change Print to PrintAndGetLoss: return loss

* change comment; add bracket

* change return type of PredictLeafIndex in boosting.h

* move string cast into lambda function

* move if-then outside predict_fun