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tqchen committed Jan 14, 2016
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==========

xgboost-0.1
===========
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* Initial release

xgboost-0.2x
============
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* Python module
* Weighted samples instances
* Initial version of pairwise rank

xgboost-0.3
===========
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* Faster tree construction module
- Allows subsample columns during tree construction via ```bst:col_samplebytree=ratio```
* Support for boosting from initial predictions
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* Add R module

xgboost-0.4
===========
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* Distributed version of xgboost that runs on YARN, scales to billions of examples
* Direct save/load data and model from/to S3 and HDFS
* Feature importance visualization in R module, by Michael Benesty
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* sklearn wrapper is supported in python module
* Experimental External memory version

on going at master
==================
xgboost-0.47
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* Changes in R library
- fixed possible problem of poisson regression.
- switched from 0 to NA for missing values.
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- added best_ntree_limit attribute, in addition to best_score and best_iteration.
* Java api is ready for use
* Added more test cases and continuous integration to make each build more robust.

on going at master
------------------

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