This is a stable release of 0.6 version

Changes

• Version 0.5 is skipped due to major improvements in the core
• Major refactor of core library.
  • Goal: more flexible and modular code as a portable library.
  • Switch to use of c++11 standard code.
  • Random number generator defaults to std::mt19937.
  • Share the data loading pipeline and logging module from dmlc-core.
  • Enable registry pattern to allow optionally plugin of objective, metric, tree constructor, data loader.
    • Future plugin modules can be put into xgboost/plugin and register back to the library.
  • Remove most of the raw pointers to smart ptrs, for RAII safety.
• Add official option to approximate algorithm tree_method to parameter.
  • Change default behavior to switch to prefer faster algorithm.
  • User will get a message when approximate algorithm is chosen.
• Change library name to libxgboost.so
• Backward compatiblity
  • The binary buffer file is not backward compatible with previous version.
  • The model file is backward compatible on 64 bit platforms.
• The model file is compatible between 64/32 bit platforms(not yet tested).
• External memory version and other advanced features will be exposed to R library as well on linux.
  • Previously some of the features are blocked due to C++11 and threading limits.
  • The windows version is still blocked due to Rtools do not support std::thread.
• rabit and dmlc-core are maintained through git submodule
  • Anyone can open PR to update these dependencies now.
• Improvements
  • Rabit and xgboost libs are not thread-safe and use thread local PRNGs
  • This could fix some of the previous problem which runs xgboost on multiple threads.
• JVM Package
  • Enable xgboost4j for java and scala
  • XGBoost distributed now runs on Flink and Spark.
• Support model attributes listing for meta data.
  • #1198
  • #1166
• Support callback API
  • #892
  • #1211
  • #1264
• Support new booster DART(dropout in tree boosting)
  • #1220
• Add CMake build system
  • #1314