GitLab

* change whitespace to underline in feature names

* add test

* fix bug

* fix bug

* warning -> fatal

* refine plot

* use warnings

* refine  logic

* revert 'move to compat.py'

* use json instead of repr/eval for pandas_categorical

* fix json dumps with numpy data

* add more test cases

* expose save model to string to c_api

* add 'save-model-to-string' to python; use it to copy model

* remove boosting_type

* add plot importance

* add plot example

* 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

* 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

* 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)

* use handle is not None for _is_constructed

* sort imports; clean code; move FAQ to docs

* simplify Dataset class

* simplify check output; fix deprecated warning

* format python code with pep8

* **DO NOT MERGE** deliberately break rules to see what will happen during check

* Revert "**DO NOT MERGE** deliberately break rules to see what will happen during check"

This reverts commit 0db93cd7a43c7efa43a2112ada43d46c6f9115d9.

* fix format in test.py

* add docs for pep-8

* add @property to sklearn interface

* add deprecated; fix binary_metric

* support pickle

* add pickle/joblib test; change test_basic to unittest

* remove file for deepcopy

* fix tests

* test basic predict from file

* Revert "test basic predict from file"

This reverts commit 60d2c3158537fd56081f60f1d6d120cedd782887.

* test predict from file

* use tempfile for copy & pickle

* use tempfile w/o binary mode

* clean test

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

* add troubleshooting

* use unittest

* update unittest version

* fix test_engine.py

* fix test_sklearn.py

* default eval_metric by subclass

* add test grid search

* remove verbose_eval

Provide a high level Dataset class for easy use.

* add feature importances in python; add pandas support

* solve best_iteration issue