GitLab

* some refactor.

* two stage sum up to reduce sum up error.

* add more two-stage sumup.

* some refactor.

* add alignment.

* change name to aligned_allocator.

* remove some useless sumup.

* fix a warning.

* add -march=native .

* remove the padding of gradients.

* no alignment.

* fix test.

* change KNumSumupGroup to 32768.

* change gcc flags.

* refine prediction logic.

* fix test.

* fix out_len in training score of Dart.

* improve predict speed for high dimension data.

* try use unordered_map for sparse prediction.

* avoid using unordered_map.

* clean code.

* fix test.

* move predict buffer to Predictor.

* refine prediction logic.

* fix test.

* fix out_len in training score of Dart.

* improve predict speed for high dimension data.

* many refactors.

* remove multi_loglossova.

* fix tests.

* avoid using lambda function.

* fix some format.

* reduce branching.

1. add csc support
2. some data type from float to double

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

Support multiclass classification (#53)

* 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