Olivier Grisel 8ad2f5ea8a ENH: Make forest prediction code more robust to mutations of the estimators list ... This can be useful to quickly study the impact of the size of the forest by subsampling from it for instance.		2013-10-30 23:35:07 +01:00
..
tests	FIX: use XorShift random number generator	2013-09-22 19:36:09 +02:00
__init__.py	ENH bagging meta-estimator	2013-09-11 13:51:09 +02:00
_gradient_boosting.c	FIX #1622: OPTIM: remove obsolete random_state instance in the Tree class	2013-10-29 11:28:12 +01:00
_gradient_boosting.pyx	MAINT: remove utf-8 headers	2013-08-26 14:55:51 +02:00
bagging.py	DOC: bootstrap=True by default	2013-09-12 08:41:22 +02:00
base.py	DOC: base_estimator_ + estimators_ in ensemble.base	2013-09-11 13:51:12 +02:00
forest.py	ENH: Make forest prediction code more robust to mutations of the estimators list	2013-10-30 23:35:07 +01:00
gradient_boosting.py	ENH: added PresortBestSplitter	2013-09-21 18:26:28 +02:00
partial_dependence.py	FIX: random number generator	2013-09-22 19:35:18 +02:00
setup.py	added gbrt extension module (faster prediction methods)	2012-03-29 08:34:45 +02:00
weight_boosting.py	AdaBoostRegressor: fix redundant recalculation of error_vect.max()	2013-10-08 20:15:41 -07:00