GitLab

* 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

* use handle is not None for _is_constructed

* sort imports; clean code; move FAQ to docs

* finish R's c_api

* clean code

* fix sizeof pointer in 32bit system.

* add predictor class

* add Dataset class

* format code

* add booster

* add type check for expose function

* add a simple callback

* add all callbacks

* finish the basic training logic

* update docs

* add an simple training interface

* add basic test

* adapt the changes in c_api

* add test for Dataset

* add test for custom obj/eval functions

* fix python test

* fix bug in metadata init

* fix R CMD check

* fix reset parameter

* redefine CVBooster

* env.model won't be None

* update env.params

* 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

* remove other parameters in sklearn fit

* add dart parameters to sklearn init

* 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

add learning rate to dart (#133)

Provide a high level Dataset class for easy use.

* add feature importances in python; add pandas support

* solve best_iteration issue

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