xgboost v0.60 Release Notes
Release Date: 2016-07-29 // over 7 years ago-
🔄 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_methodto 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.
- 👌 Support callback API
- 👌 Support new booster DART(dropout in tree boosting)
- ➕ Add CMake build system