GitLab

* Attempt to fix categorical issue in R package

* Add small fix for categorical IDs

* Add error for unknown numbers/columns

* fix bug for categorical_feature

* add test on load model with categorical feature

* add unseen category in test dataset

* save/load pandas_categorical to model

* fix logic

* cast pandas columns to string

* add load pandas_categorical from file to _InnerPredictor init

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

* Added CMake option to create dylib on MacOS

sklearn compatibility update- renames .feature_importance_ to .featur…

minor typo fixes

* suppprt pandas categorical

* refine logic

* make default=auto

* fix train/valid categorical codes

* add test

* unify set _predictor

* fix tests

* fix warning

* support feature_name=int

* 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

* add compat.py

* unify types

* range/xrange -> range_

* move argc_ to compat.py; add is_numeric error type

* use simplejson for json

* move json to compat.py

* move pandas to compat.py

* move sklearn to compat.py

* remove unused function

* fix 'unify types'

* argc_ (lambda -> def)

* add pmml to test

* refine pmml.py

* use ~n instead of -n-1

* change map to list comprehension

* fix check

* fix 'use ~n instead of -n-1'

* fix exception