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8 Commits

Author SHA1 Message Date
Raghav R V f67e911124 DOC Modify documentation/examples for the new model_selection module 2015-10-29 16:49:23 +01:00
MechCoder c31de116f9 Fix broken examples using RandomTreeEmbeddings 
RandomTreeEmbeddings overwrites the fit_transform method of
_LearntSelectorMixin
 2015-10-16 12:44:04 -04:00
MechCoder 5a0db1717a 1. Added parameter prefit to pass in a fitted estimator. 
2. Use assert_warns instead of catch_warnings
3. Remove depracation warnings in common tests.
 2015-10-09 01:57:36 -04:00
MechCoder 2ee718cc75 Add narrative docs and fix examples 2015-10-05 11:25:06 -04:00
Jacob Schreiber bc225a5e1a ENH apply method added to Gradient Boosting 2015-09-10 10:32:51 +02:00
Alexandre Gramfort 6126eced61 unused import 2015-08-31 21:52:48 +02:00
Tim Head ea8d092f2c Explicitly mention RandomTreesEmbedding in the text 2015-08-14 20:04:46 +02:00
Tim Head 89ec72ea2f Example to demonstrate use of tree.apply() method 
This example trains several tree based ensemble methods and uses
them to transform the data into a high dimensional, sparse space.
The trains a linear model on this new feature space. The idea is
taken from:

Practical Lessons from Predicting Clicks on Ads at Facebook Junfeng Pan,
He Xinran, Ou Jin, Tianbing XU, Bo Liu, Tao Xu, Yanxin Shi, Antoine
Atallah, Ralf Herbrich, Stuart Bowers, Joaquin Quiñonero Candela
International Workshop on Data Mining for Online Advertising (ADKDD)

https://www.facebook.com/publications/329190253909587/
 2015-08-11 20:38:07 +02:00