Release 0.3
Major Features and Improvements
FederatedML
- Support OneVsALL for multi-label classification task
- Add trash-recycle in Hetero Logistic Regression
- Add numeric stable for sigmoid and log_logistic function.
- Support different calculation mode in Hetero Logistic Regression and Hetero SecureBoost
- Decouple Federated Feature Binning and Federated Feature Selection
- Add feature importance calculation in Hetero SecureBoost
- Add multi-host in Hetero SecureBoost
- Support tag:value sparse format input data
- Support output intersect-id with feature-instance in Intersection
- Support OneHot encoding module.
- Support bucket binning for Federated Feature Binning.
- Support add, sub, mul, div ,gt, lt ,eq, etc mathematical operator on Fixed-Point data
- Add authority validation for parameter setting
FATE-Serving
- Add multi-level cache for multi-party inference result
- Add startInferceJob and getInferenceResult interfaces to support the inference process asynchronization
- Normalized inference return code
- Real-time logging of inference summary logs and inferential detail logs
- Improve the loading of the pre and post processing adapter and data access adapter for host
EggRoll
- New computing and storage APIs
- Stability optimizations
- Performance optimizations
- Storage usage improvements
Example
- Add Mini-FederatedML test task example
- Using task manager to submit a distributed task for current examples
Bug Fixes and Other Changes
- fix detect onehot max column overflow bug.
- fix dataio dense format not reading host data header bug.
- fix bugs of call of statistics function
- fix bug for federated feature selection that at least one feature remains for each party
- Not allowing so small batch size in LR module for safety consideration.
- fix naming error in federated feature selection module.
- Fix the bug of automated publishing model information in some extreme cases
- Fixed some overflow bugs in fixed-point data
- fix many other bugs.