WInte.r version 1.3
Added new logging and debugging features for:
- Blocking
- Matching
- Data Fusion
Added new facade classes for data normalisation:
- The ValueNormaliser can be used to transform string values into various data types and interpret units of measurement
- The DataSetNormaliser can detect data types and transform complete datasets into a normalised format
WekaMatchingRule:
- Added support for external models (e.g. learned with RapidMiner) using the PMML format
- Added access to the model's description and performance after training
- Improved export of generated features for external model learning
Extended Web Tables data model:
- Added join
- Improved projection
- Improved support for functional dependencies and candidate keys
Further changes:
- Improved parallel processing in ParallelProcessable
- Added framework extension: Metanome Integration
- Added a detailed tutorial on how to use WInte.r for data integration